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Recently, photovoltaic (PV) with energy storage systems (ESS) have been widely adopted in buildings to overcome growing power demands and earn financial benefits. The overall energy cost can be optimized by combining a well-sized hybrid PV/ESS system with an efficient energy management system (EMS). Generally, EMS is implemented within the overall functions of the Building Automation System (BAS). However, due to its limited computing resources, BAS cannot handle complex algorithms that aim to optimize energy use in real-time under different operating conditions. Furthermore, islanding the building's local network to maximize the PV energy share represents a challenging task due to the potential technical risks. In this context, this article addresses an improved approach based on upgrading the BAS data analytics capability by means of an edge computing technology. The edge communicates with the BAS low-level controller using a serial communication protocol. Taking advantage of the high computing ability of the edge device, an optimization-based EMS of the PV/ESS hybrid system is implemented. Different testing scenarios have been carried out on a real prototype with different weather conditions, and the results show the implementation feasibility and technical performance of such advanced EMS for the management of building energy resources. It has also been proven to be feasible and advantageous to operate the local energy network in island mode while ensuring system safety. Additionally, an estimated energy saving improvement of 6.23 % has been achieved using optimization-based EMS compared to the classical rule-based EMS, with better ESS constraints fulfillment.
For the treatment of bone defects, biodegradable, compressive biomaterials are needed as replacements that degrade as the bone regenerates. The problem with existing materials has either been their insufficient mechanical strength or the excessive differences in their elastic modulus, leading to stress shielding and eventual failure. In this study, the compressive strength of CPC ceramics (with a layer thickness of more than 12 layers) was compared with sintered β-TCP ceramics. It was assumed that as the number of layers increased, the mechanical strength of 3D-printed scaffolds would increase toward the value of sintered ceramics. In addition, the influence of the needle inner diameter on the mechanical strength was investigated. Circular scaffolds with 20, 25, 30, and 45 layers were 3D printed using a 3D bioplotter, solidified in a water-saturated atmosphere for 3 days, and then tested for compressive strength together with a β-TCP sintered ceramic using a Zwick universal testing machine. The 3D-printed scaffolds had a compressive strength of 41.56 ± 7.12 MPa, which was significantly higher than that of the sintered ceramic (24.16 ± 4.44 MPa). The 3D-printed scaffolds with round geometry reached or exceeded the upper limit of the compressive strength of cancellous bone toward substantia compacta. In addition, CPC scaffolds exhibited more bone-like compressibility than the comparable β-TCP sintered ceramic, demonstrating that the mechanical properties of CPC scaffolds are more similar to bone than sintered β-TCP ceramics.
Human interaction frequently includes decision-making processes during which interactants call on verbal and non-verbal resources to manage the flow of interaction. In 2017, Stevanovic et al. carried out pioneering work, analyzing the unfolding of moment-by-moment dynamics by investigating the behavioral matching during search and decision-making phases. By studying the similarities in the participant's body sway during a conversation task in Finnish, the authors showed higher behavioral matching during decision phases than during search phases. The purpose of this research was to investigate the whole-body sway and its coordination during joint search and decision-making phases as a replication of the study by Stevanovic et al. (2017) but based on a German population. Overall, 12 dyads participated in this study and were asked to decide on 8 adjectives, starting with a pre-defined letter, to describe a fictional character. During this joint-decision task (duration: 206.46 ± 116.08 s), body sway of both interactants was measured using a 3D motion capture system and center of mass (COM) accelerations were computed. Matching of body sway was calculated using a windowed cross correlation (WCC) of the COM accelerations. A total of 101 search and 101 decision phases were identified for the 12 dyads. Significant higher COM accelerations (5.4*10−3 vs. 3.7*10−3 mm/s2, p < 0.001) and WCC coefficients (0.47 vs. 0.45, p = 0.043) were found during decision-making phases than during search phases. The results suggest that body sway is one of the resources humans use to communicate the arrival at a joint decision. These findings contribute to a better understanding of interpersonal coordination from a human movement science perspective.
Background/Purpose
Several methods are used to evaluate the outcome of total hip arthroplasty (THA), however, their relationship at different time points after surgery is unclear. The purpose of this exploratory study was to investigate correlations between self-report function, performance-based tests (PBTs) and biomechanical parameters in patients 12 months after THA.
Methods
Eleven patients were included in this preliminary cross-sectional study. Hip disability and Osteoarthritis Outcome Score (HOOS) was completed for self-reported function. As PBTs, the Timed-up-and-Go test (TUG) and 30-Second-Chair-Stand test (30CST) were used. Biomechanical parameters were derived from analyses of hip strength, gait and balance. Potential correlations were calculated using Spearman correlation coefficient r.
Results
HOOS scores and parameters of PBTs showed moderate to strong correlations (0.3 < r < 0.7). Correlation analysis between HOOS scores and biomechanical parameters revealed moderate to strong correlations for hip strength whereas correlations with gait parameters and balance were rather weak (r < 0.3). Moderate to strong correlations were also found between parameters of hip strength and 30CST.
Conclusion
For THA outcome assessment 12 months after surgery, our first results indicate that self-report measures or PBTs could be used. Analysis of hip strength also appears to be reflected in HOOS and PBT parameters and may be considered as an adjunct. Given the weak correlations with gait and balance parameters, we suggest that gait analysis and balance testing should be performed in addition to PROMs and PBTs as they may provide supplementary information, especially for THA patients that are at risk for falls.
Optimization of energetic refurbishment roadmaps for multi-family buildings utilizing heat pumps
(2023)
A novel methodology for calculating optimized refurbishment roadmaps is developed in this paper. The aim of the roadmaps is to determine when and how should which component of the building envelope and heat generation system be refurbished to achieve the lowest net present value. The integrated optimization approach couples a particle swarm optimization algorithm with a dynamic building simulation of the building envelope and the heat supply system. Due to a free selection of implementation times and refurbishment depth, the optimization method achieves the lowest net present value and high CO2 reduction and is therefore an important contribution to achieve climate neutrality in the building stock.
The method is exemplarily applied to a multi-family house built in 1970. In comparison to a standard refurbishment roadmap, cost savings of 6–16 % and CO2 savings of 6–59 % are possible. The sensitivity of the refurbishment roadmap measures is analyzed on the basis of a parametric analysis. Robust optimization results are obtained with a mean refurbishment level of approx. 50 kWh/m2/a of the building envelope. The preferred heat generation system is a bivalent brine-heat pump system with a share of 70 % of the heat load being covered by the electric heat pump.
Am 1. Juli 2022 trafen sich im Rahmen des Abschlusskolloquiums des Projekts ACA-Modes rund 60 Teilnehmende aus Forschung, Lehre und Industrie zu einer internationalen Konferenz an der Hochschule Offenburg. Hier wurden die Projektergebnisse rund um die erfolgreiche Implementierung modellprädiktiver Regelstrategien vorgestellt, aktuelle Fragestellungen diskutiert und Entwicklungspfade hin zu einem netzdienlichen Betrieb von Energieverbundsystemen skizziert.
Heat pumps play a central role in decarbonizing the heat supply of buildings. However, in this article, implementing heat pumps in existing buildings, a significant challenge is still presented due to high temperature requirements. In this article, a systematic analysis of the effects of heat source temperatures, maximum heat pump condenser temperatures, and system temperatures on the seasonal performance of heat pump (HP) systems is presented. The quantitative performance analysis encompasses over 50 heat pumps installed in residential buildings, revealing correlations between the building characteristics, observed temperatures, and heat pump type. The performance of an HP system retrofitted to a 30-dwelling multifamily building is presented in more detail. The bivalent HP system combines air and ground as heat sources and achieves a seasonal performance factor of 3.25 with a share of the gas boiler of 27% in its first year of operation. In these findings, the technical feasibility of retrofitting heat pumps is demonstrated in existing buildings and insights are provided into overcoming the challenges associated with high temperature requirements.
Lithium-ion batteries exhibit slow voltage dynamics on the minute time scale that are usually associated with transport processes. We present a novel modelling approach toward these dynamics by combining physical and data-driven models into a Grey-box model. We use neural networks, in particular neural ordinary differential equations. The physical structure of the Grey-box model is borrowed from the Fickian diffusion law, where the transport domain is discretized using finite volumes. Within this physical structure, unknown parameters (diffusion coefficient, diffusion length, discretization) and dependencies (state of charge, lithium concentration) are replaced by neural networks and learnable parameters. We perform model-to-model comparisons, using as training data (a) a Fickian diffusion process, (b) a Warburg element, and (c) a resistor-capacitor circuit. Voltage dynamics during constant-current operation and pulse tests as well as electrochemical impedance spectra are simulated. The slow dynamics of all three physical models in the order of ten to 30 min are well captured by the Grey-box model, demonstrating the flexibility of the present approach.
This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics aging model of a 500 mAh high-energy lithium-ion pouch cell with graphite negative electrode and lithium nickel manganese cobalt oxide (NMC) positive electrode. This model includes electrochemical reactions for solid electrolyte interphase (SEI) formation at the graphite negative electrode, lithium plating, and SEI formation on plated lithium. The thermodynamics of the aging reactions are modeled depending on temperature and ion concentration and the reactions kinetics are described with an Arrhenius-type rate law. Good agreement of model predictions with galvanostatic charge/discharge measurements and electrochemical impedance spectroscopy is observed over a wide range of operating conditions. The model allows to quantify capacity loss due to cycling near beginning-of-life as function of operating conditions and the visualization of aging colormaps as function of both temperature and C-rate (0.05 to 2 C charge and discharge, −20 °C to 60 °C). The model predictions are also qualitatively verified through voltage relaxation, cell expansion and cell cycling measurements. Based on this full model, six different aging indicators for determination of the limits of fast charging are derived from post-processing simulations of a reduced, pseudo-two-dimensional isothermal model without aging mechanisms. The most successful aging indicator, compared to results from the full model, is based on combined lithium plating and SEI kinetics calculated from battery states available in the reduced model. This methodology is applicable to standard pseudo-two-dimensional models available today both commercially and as open source.
Im Automobilbau bietet der Einsatz der Multimaterialbauweise ein signifikantes Potenzial zur Gewichtsreduktion. Zugleich erfordert diese Bauweise eine große Anzahl von Fügeverfahren für die Verbindung der unterschiedlichen Werkstoffe und Werkstoffklassen. Dabei muss eine Vielzahl an konstruktiven und materialseitigen Anforderungen berücksichtigt werden. Um in diesem Auswahlprozess den Aspekt des Leichtbaus beim Fügeverfahren selbst systematisch zu integrieren, wurde eine Methodik entwickelt, welche die Fügeverfahren im Hinblick auf ihr jeweiliges Leichtbaupotenzial bewertet.
Phytases are widely used food and feed enzymes to improve phosphate availability and reduce anti-nutritional factors. Despite the benefits, enzyme usage is restricted by the harsh conditions in a gastrointestinal tract (pH 2–6) and feed pelleting conditions at high temperatures (60–90 °C). The commercially available phytase Quantum® Blue has been immobilized as CLEAs using glutardialdehyde and soy protein resulting in a residual activity of 33%. The influence of the precipitating agent, precipitant concentration, cross-linker concentration and cross-linking time, sodium borohydride as well as the proteic feeders gluten, soy protein and bovine serum albumin (BSA) has been optimized. The best conditions were 90% (v/v) ethyl lactate as precipitating reagent, 100 mM glutardialdehyde and a soy protein concentration of 227 mg/L with a cross-linking time of 1 h. The intrinsically stable phytase remained its high thermal stability and temperature optimum. The phytase-CLEA achieved a 425% increase of residual activity under harsh acidic conditions between pH 2.2 and 3.5 compared to the free enzyme. The free and immobilized phytase were deployed in an in vitro assay simulating the acidic conditions in the gizzard of poultry at pH 2. The hydrolysis of phytate was monitored using a novel high-performance thin-layer chromatography (HPTLC) analysis and DAD scanner to study the InsPx fingerprint. All lower inositol phosphate pools (InsP1–InsP6) and free phosphate were separated and analyzed. The phytase-CLEA efficiently released 80% of the total phosphate within 180 min, whereas the free enzyme only released 6% in the same time under the same conditions.
Wirtschaftlichkeitsbetrachtung eines smarten Energiekonzepts für ein Bestandsquartier in Karlsruhe
(2023)
Die Transformation der Energieversorgung in Bestandsgebäuden ist für die Erreichung der Klimaziele im Gebäudesektor entscheidend. In einem modellhaften Quartiersprojekt in Karlsruhe-Durlach wird ein ‚smartes Energiekonzept‘, bestehend aus Wärmepumpen, Blockheizkraftwerk und PV-Anlagen mit lokalem Strom- und Wärmenetz umgesetzt und messtechnisch begleitet. Ziel ist dabei eine CO2-effiziente und wirtschaftliche Bereitstellung von Wärme und Strom.
In dem Artikel wird eine Wirtschaftlichkeitsbetrachtung für das Wärme- und Stromcontracting auf Basis der realen Investitionskosten sowie der gemessenen und berechneten Energieflüsse durchgeführt. Die Wärmegestehungskosten hängen neben den Investitionskosten von den energiewirtschaftlichen Rahmenbedingungen ab. Mit ansteigender CO2-Steuer werden mittelfristig Wärmegestehungskosten erreicht, die unter denen konventioneller Energiesysteme liegen. Dadurch bietet das integrierte Energiekonzept ein breites Anwendungspotenzial für städtische Bestandsquartiere außerhalb von Fernwärme-Gebieten.
Predictive control has great potential in the home energy management domain. However, such controls need reliable predictions of the system dynamics as well as energy consumption and generation, and the actual implementation in the real system is associated with many challenges. This paper presents the implementation of predictive controls for a heat pump with thermal storage in a real single-family house with a photovoltaic rooftop system. The predictive controls make use of a novel cloud camera-based short-term solar energy prediction and an intraday prediction system that includes additional data sources. In addition, machine learning methods were used to model the dynamics of the heating system and predict loads using extensive measured data. The results of the real and simulated operation will be presented.
Purpose
To (1) identify neuromuscular and biomechanical injury risk factors in elite youth soccer players and (2) assess the predictive ability of a machine learning approach.
Material and Methods
Fifty-six elite male youth soccer players (age: 17.2 ± 1.1 years; height: 179 ± 8 cm; mass: 70.4 ± 9.2 kg) performed a 3D motion analysis, postural control testing, and strength testing. Non-contact lower extremities injuries were documented throughout 10 months. A least absolute shrinkage and selection operator (LASSO) regression model was used to identify the most important injury predictors. Predictive performance of the LASSO model was determined in a leave-one-out (LOO) prediction competition.
Results
Twenty-three non-contact injuries were registered. The LASSO model identified concentric knee extensor peak torque, hip transversal plane moment in the single-leg drop landing task and center of pressure sway in the single-leg stance test as the three most important predictors for injury in that order. The LASSO model was able to predict injury outcomes with a likelihood of 58% and an area under the ROC curve of 0.63 (sensitivity = 35%; specificity = 79%).
Conclusion
The three most important variables for predicting the injury outcome suggest the importance of neuromuscular and biomechanical performance measures in elite youth soccer. These preliminary results may have practical implications for future directions in injury risk screening and planning, as well as for the development of customized training programs to counteract intrinsic injury risk factors. However, the poor predictive performance of the final model confirms the challenge of predicting sports injuries, and the model must therefore be evaluated in larger samples.
Bewegungsanalysesysteme in der Forschung und für niedergelassene Orthopädinnen und Orthopäden
(2023)
Hintergrund
Komplexe biomechanische Bewegungsanalysen können für eine Vielzahl orthopädischer Fragestellungen wichtige Informationen liefern. Bei der Beschaffung von Bewegungsanalysesystemen sind neben den klassischen Messgütekriterien (Validität, Reliabilität, Objektivität) auch räumliche und zeitliche Rahmenbedingungen sowie Anforderungen an die Qualifikation des Messpersonals zu berücksichtigen.
Anwendung
In der komplexen Bewegungsanalyse werden Systeme zur Bestimmung der Kinematik, der Kinetik und der Muskelaktivität (Elektromyographie) eingesetzt. Der vorliegende Artikel gibt einen Überblick über Methoden der komplexen biomechanischen Bewegungsanalyse für den Einsatz in der orthopädischen Forschung oder in der individuellen Patientenversorgung. Neben dem Einsatz zur reinen Bewegungsanalyse wird auch der Einsatz von Bewegungsanalyseverfahren im Bereich des Biofeedbacktrainings diskutiert.
Beschaffung
Für die konkrete Anschaffung von Bewegungsanalysesystemen empfiehlt sich die Kontaktaufnahme mit Fachgesellschaften (z. B. Deutsche Gesellschaft für Biomechanik), Hochschulen und Universitäten mit vorhandenen Bewegungsanalyseeinrichtungen oder Vertriebsfirmen im Bereich der Biomechanik.
Background
Internal tibial loading is influenced by modifiable factors with implications for the risk of stress injury. Runners encounter varied surface steepness (gradients) when running outdoors and may adapt their speed according to the gradient. This study aimed to quantify tibial bending moments and stress at the anterior and posterior peripheries when running at different speeds on surfaces of different gradients.
Methods
Twenty recreational runners ran on a treadmill at 3 different speeds (2.5 m/s, 3.0 m/s, and 3.5 m/s) and gradients (level: 0%; uphill: +5%, +10%, and +15%; downhill: –5%, –10%, and –15%). Force and marker data were collected synchronously throughout. Bending moments were estimated at the distal third centroid of the tibia about the medial–lateral axis by ensuring static equilibrium at each 1% of stance. Stress was derived from bending moments at the anterior and posterior peripheries by modeling the tibia as a hollow ellipse. Two-way repeated-measures analysis of variance were conducted using both functional and discrete statistical analyses.
Results
There were significant main effects for running speed and gradient on peak bending moments and peak anterior and posterior stress. Higher running speeds resulted in greater tibial loading. Running uphill at +10% and +15% resulted in greater tibial loading than level running. Running downhill at –10% and –15% resulted in reduced tibial loading compared to level running. There was no difference between +5% or –5% and level running.
Conclusion
Running at faster speeds and uphill on gradients ≥+10% increased internal tibial loading, whereas slower running and downhill running on gradients ≥–10% reduced internal loading. Adapting running speed according to the gradient could be a protective mechanism, providing runners with a strategy to minimize the risk of tibial stress injuries.
Der prozentuale Energieaufwand für die Warmwasserbereitung ist umso höher, je geringer der Bedarf an Raumwärme – erreicht durch besser gedämmte Gebäudehüllen – ist. Gleichzeitig kann dieser Aufwand für Warmwasser aufgrund der normativ geforderten Systemtemperaturen von 60/55 °C bei zentraler Warmwasserbereitung über Wärmepumpen nur vergleichsweise energieaufwendig abgedeckt werden. Eine Studie des Fraunhofer ISE zeigt, wie groß dieser Temperatur-Effekt im Vergleich unterschiedlicher Trinkwasser-Erwärmungssysteme ist.
Photovoltaic thermal (PVT) technology has been drawing attention recently. Electrification of the heating sector with heat pumps run by carbon-free electricity sources like photovoltaics is setting the ground for the interest. This article gives insight into PVT technologies and collector designs according to application and operating temperatures. For most conventional designs, examples like prototypes from Research & Development projects are presented. In addition, commercial products are listed along these categories, and the influence on the gross thermal and electrical yield is depicted based on Solar Keymark certification data. The process of certification is presented in a comprehensive way, showing current limitations, giving an outlook on the most recent approach for enhanced procedures and specifications. Finally, different system layouts are presented, and examples from installations combined with a heat pump are given with their specific performances. Real performance data of several PVT installations are compared to conventional heat pump systems. The identified seasonal performance factors are in a range from 3.4 to 4.2 and in between air source and ground source heat pumps. Continuous monitoring and derived data are enablers to discover the decisive influence of the system layout and dimensioning on performance indicators like, for example, operating temperatures over the year.
Purpose
To summarize the mechanical loading of the spine in different activities of daily living and sports.
Methods
Since the direct measurement is not feasible in sports activities, a mathematical model was applied to quantify spinal loading of more than 600 physical tasks in more than 200 athletes from several sports disciplines. The outcome is compression and torque (normalized to body weight/mass) at L4/L5.
Results
The data demonstrate high compressive forces on the lumbar spine in sport-related activities, which are much higher than forces reported in normal daily activities and work tasks. Especially ballistic jumping and landing skills yield high estimated compression at L4/L5 of more than ten times body weight. Jumping, landing, heavy lifting and weight training in sports demonstrate compression forces significantly higher than guideline recommendations for working tasks.
Conclusion
These results may help to identify acute and long-term risks of low back pain and, thus, may guide the development of preventive interventions for low back pain or injury in athletes.
Footwear plays a critical role in our daily lives, affecting our performance, health and overall well-being. Well-designed footwear can provide protection, comfort and improved foot functionality, while poorly designed footwear can lead to mobility problems and declines in physical activity. The overall goal of footwear research is to provide a scientific basis for professionals in the field to provide an optimal footwear solution for a given person, for a given task, in a given environment, while using sustainable manufacturing processes. This article suggests potential directions for future research with a focus on athletic footwear biomechanics. Directions include the evidence-based individualisation of footwear, the interaction between design and prolonged use, and improving the sustainability of footwear. The authors also provide a speculative outlook on methodological developments that may provide greater insight into these areas. These developments may include: (1) the use of larger scale, real-world and representative data, (2) the use of 3D printing to create experimental footwear, (3) the advancement of in silico research methods, and (4) furthering multidisciplinary collaboration. If successfully applied in the future, footwear research will contribute to active and healthy lifestyles across the lifespan.
Appraising the Methodological Quality of Sports Injury Video Analysis Studies: The QA-SIVAS Scale
(2023)
Background
Video analysis (VA) is commonly used in the assessment of sports injuries and has received considerable research interest. Until now, no tool has been available for the assessment of study quality. Therefore, the objective of this study was to develop and evaluate a valid instrument that reliably assesses the methodological quality of VA studies.
Methods
The Quality Appraisal for Sports Injury Video Analysis Studies (QA-SIVAS) scale was developed using a modified Delphi approach including expert consensus and pilot testing. Reliability was examined through intraclass correlation coefficient (ICC3,1) and free-marginal kappa statistics by three independent raters. Construct validity was investigated by comparing QA-SIVAS with expert ratings by using Kendall’s tau analysis. Rating time was studied by applying the scale to 21 studies and computing the mean time for rating per study article.
Results
The QA-SIVAS scale consists of an 18-item checklist addressing the study design, data source, conduct, report, and discussion of VA studies in sports injury research. Inter- and intra-rater reliability were excellent with ICCs > 0.97. Expert ratings revealed a high construct validity (0.71; p < 0.001). Mean rating time was 10 ± 2 min per article.
Conclusion
QA-SIVAS is a reliable and valid instrument that can be easily applied to sports injury research. Future studies in the field of VA should adhere to standardized methodological criteria and strict quality guidelines.
Injury prevention is essential in running due to the risk of overuse injury development. Tailoring running shoes to individual needs may be a promising strategy to reduce this risk. Novel manufacturing processes allow the production of individualised running shoes that incorporate features that meet individual biomechanical and experiential needs. However, specific ways to individualise footwear to reduce injury risk are poorly understood. Therefore, this scoping review provides an overview of (1) footwear design features that have the potential for individualisation; and (2) the literature on the differential responses to footwear design features between selected groups of individuals. These purposes focus exclusively on reducing the risk of overuse injuries. We included studies in the English language on adults that analysed: (1) potential interaction effects between footwear design features and subgroups of runners or covariates (e.g., age, sex) for running-related biomechanical risk factors or injury incidences; (2) footwear comfort perception for a systematically modified footwear design feature. Most of the included articles (n = 107) analysed male runners. Female runners may be more susceptible to footwear-induced changes and overuse injury development; future research should target more heterogonous sampling. Several footwear design features (e.g., midsole characteristics, upper, outsole profile) show potential for individualisation. However, the literature addressing individualised footwear solutions and the potential to reduce biomechanical risk factors is limited. Future studies should leverage more extensive data collections considering relevant covariates and subgroups while systematically modifying isolated footwear design features to inform footwear individualisation.
Maintaining stability while walking on arbitrary surfaces or dealing with external perturbations is of great interest in humanoid robotics research. Increasing the system’s autonomous robustness to a variety of postural threats during locomotion is the key despite the need to evaluate noisy sensor signals. The equations of motion are the foundation of all published approaches. In contrast, we propose a more adequate evaluation of the equations of motion with respect to an arbitrary moving reference point in a non-inertial reference frame. Conceptual advantages are, e.g., getting independent of global position and velocity vectors estimated by sensor fusions or calculating the imaginary zero-moment point walking on different inclined ground surfaces. Further, we improve the calculation results by reducing noise-amplifying methods in our algorithm and using specific characteristics of physical robots. We use simulation results to compare our algorithm with established approaches and test it with experimental robot data.
In 4D printing, an additively manufactured component is given the ability to change its shape or function in an intended and useful manner over time. The technology of 4D printing is still in an early stage of development. Nevertheless, interesting research and initial applications exist in the literature. In this work, a novel methodical approach is presented that helps transfer existing 4D printing research results and knowledge into solving application tasks systematically. Moreover, two different smart materials are analyzed, used, and combined following the presented methodical approach to solving the given task in the form of recovering an object from a poorly accessible space. This is implemented by self-positioning, grabbing, and extracting the target object. The first smart material used to realize these tasks is a shape-memory polymer, while the second is a polymer-based magnetic composite. In addition to the presentation and detailed implementation of the methodical approach, the potentials and behavior of the two smart materials are further examined and narrowed down as a result of the investigation. The results show that the developed methodical approach contributes to moving 4D printing closer toward a viable alternative to existing technologies due to its problem-oriented nature.
Immunosorbent turnip vein clearing virus (TVCV) particles displaying the IgG-binding domains D and E of Staphylococcus aureus protein A (PA) on every coat protein (CP) subunit (TVCVPA) were purified from plants via optimized and new protocols. The latter used polyethylene glycol (PEG) raw precipitates, from which virions were selectively re-solubilized in reverse PEG concentration gradients. This procedure improved the integrity of both TVCVPA and the wild-type subgroup 3 tobamovirus. TVCVPA could be loaded with more than 500 IgGs per virion, which mediated the immunocapture of fluorescent dyes, GFP, and active enzymes. Bi-enzyme ensembles of cooperating glucose oxidase and horseradish peroxidase were tethered together on the TVCVPA carriers via a single antibody type, with one enzyme conjugated chemically to its Fc region, and the other one bound as a target, yielding synthetic multi-enzyme complexes. In microtiter plates, the TVCVPA-displayed sugar-sensing system possessed a considerably increased reusability upon repeated testing, compared to the IgG-bound enzyme pair in the absence of the virus. A high coverage of the viral adapters was also achieved on Ta2O5 sensor chip surfaces coated with a polyelectrolyte interlayer, as a prerequisite for durable TVCVPA-assisted electrochemical biosensing via modularly IgG-assembled sensor enzymes.
This paper presents a framework for numerical building validation enhancement based on detailed building specifications from in-situ measurements and evidence-based validation assessment undertaken on a detached sustainable lightweight building in a semi-arid climate. The validation process has been undergone in a set of controlled experiments – a free-float period, and steady-state internal temperatures. The validation was conducted for a complete year with a 1-min time step for the hourly indoor temperature and the variable refrigerant flow (VRF) energy consumption. The initial baseline model was improved by three series of validation steps per three different field measurements including thermal transmittance, glazing thermal and optical properties, and airtightness. Then, the accurate and validated model was used for building energy efficiency assessment in 12 regions of Morocco. This study aims to assess the effect of accurate building characteristics values on the numerical model enhancement. The initial CV(RMSE) and NMBE have improved respectively from 14.58 % and −11.23 %–7.85 % and 1.86 % for the indoor temperature. Besides, from 31.17 % to 14.37 %–20.57 % and 9.77 % for energy consumption. The findings demonstrate that the lightweight construction with the use of a variable refrigerant flow system could be energy efficient in the southern regions of Morocco.
Energy efficiency and hygrothermal performance of hemp clay walls for Moroccan residential buildings
(2023)
Hemp-based building envelopes have gained significant popularity in developed countries, and now the trend of constructing houses with hemp-clay blocks is spreading to developing countries like Morocco. Investigating the hygrothermal behavior of such structures under actual climate conditions is essential for advancing and promoting this sustainable practice. This paper presents an in-depth experimental characterization of a commercial hemp-clay brick that has been exposed to the outdoor environment for four years, in addition to field measurements on a building scale demonstration prototype. Additionally, the study simulates 17 representative cities to assess the hygrothermal performance and energy-saving potential in each of Morocco's six existing climate zones, using the EnergyPlus engine. The experimental campaign's findings demonstrate excellent indoor air temperature and relative humidity regulation within the hemp-clay wall building, leading to satisfactory levels of thermal comfort within hemp-clay wall buildings. This is attributed to the material's good thermal conductivity and excellent moisture buffering capacity (found to be 0.31 W/mK and 2.25 g/m2%RH), respectively). The energy simulation findings also point to significant energy savings, with cooling and heating energy reductions ranging from 27.7% to 47.5% and 33.7% to 79.8%, respectively, as compared to traditional Moroccan buildings.
Given the looming threats of climate change and the rapid worldwide urbanization, it is a necessity to prioritize the transition towards a carbon-free built environment. This research study provides a holistic digital methodology for parametric design of urban residential buildings with regard to the Mediterranean semi-arid climate zone of Morocco in the early design phase. The morphological parameters of the urban residential buildings, namely the buildings’ typology, the distance between buildings, the urban grid’s orientation, and the window-towall ratio, are evaluated in order to identify the key combinations of passive and active solar design strategies that determine the high energy performing configurations, based on the introduced Energy Performance Index (EPI), which is the ratio between solar BIPV production to maximum available installed BIPV capacity and the normalized thermal energy needs. Through an automated processing of 2187 iterations via Grasshopper, we simulate daylight autonomy, indoor thermal comfort and solar rooftop photovoltaic and building integrated photovoltaic (BIPV) energy potential. Then, we analyze the conflicting objectives of energy efficiency measures, active solar design strategies, and indoor visual comfort in the decision-making process that supports our goal of getting closer to net zero urban residential buildings. The digital workflow showed interesting trends in reaching a balanced equilibrium between performance metrics influenced by the contrasting impact of solar exposure on indoor daylight autonomy and thermal energy demand. Furthermore, the study’s findings indicate that it is possible to achieve an annual load match exceeding 66,56 % while simultaneously ensuring an acceptable visual indoor comfort (sDA higher than 0.4). The findings also highlight the important role of the BIPV system in shifting towards the net zero energy goal, by contributing up to 30 % of the overall solar energy output and covering up to 20 % of the yearly self-consumption. Moreover, the energy balance evaluation on an hourly basis indicates that BIPV system notably enhances the daily load cover factor by up to 5.5 %, particularly in the case of slab SN typology, throughout the different seasons. Graphical representations of the yearly, monthly and hourly load matches and the hourly energy balance of the best performing configurations provide a thorough understanding of the potential evolution of the urban energy system over time as a result of the gradual integration of active solar electricity production.
Lithium-ion battery cells exhibit a complex and nonlinear coupling of thermal, electrochemical,and mechanical behavior. In order to increase insight into these processes, we report the development of a pseudo-three-dimensional (P3D) thermo-electro-mechanical model of a commercial lithium-ion pouch cell with graphite negative electrode and lithium nickel cobalt aluminum oxide/lithium cobalt oxide blend positive electrode. Nonlinear molar volumes of the active materials as function of lithium stoichiometry are taken from literature and implemented into the open-source software Cantera for convenient coupling to battery simulation codes. The model is parameterized and validated using electrical, thermal and thickness measurements over a wide range of C-rates from 0.05 C to 10 C. The combined experimental and simulated analyses show that thickness change during cycling is dominated by intercalation-induced swelling of graphite, while swelling of the two blend components partially cancel each other. At C-rates above 2 C, electrochemistry-induced temperature increase significantly contributes to cell swelling due to thermal expansion. The thickness changes are nonlinearly distributed over the thickness of the electrode pair due to gradients in the local lithiation, which may accelerate local degradation. Remaining discrepancies between simulation and experiment at high C-rates might be attributed to lithium plating, which is not considered in the model at present.
A balcony photovoltaic (PV) system, also known as a micro-PV system, is a small PV system consisting of one or two solar modules with an output of 100–600 Wp and a corresponding inverter that uses standard plugs to feed the renewable energy into the house grid. In the present study we demonstrate the integration of a commercial lithium-ion battery into a commercial micro-PV system. We firstly show simulations over one year with one second time resolution which we use to assess the influence of battery and PV size on self-consumption, self-sufficiency and the annual cost savings. We then develop and operate experimental setups using two different architectures for integrating the battery into the micro-PV system. In the passive hybrid architecture, the battery is in parallel electrical connection to the PV module. In the active hybrid architecture, an additional DC-DC converter is used. Both architectures include measures to avoid maximum power point tracking of the battery by the module inverter. Resulting PV/battery/inverter systems with 300 Wp PV and 555 Wh battery were tested in continuous operation over three days under real solar irradiance conditions. Both architectures were able to maintain stable operation and demonstrate the shift of PV energy from the day into the night. System efficiencies were observed comparable to a reference system without battery. This study therefore demonstrates the feasibility of both active and passive coupling architectures.
Electrochemical pressure impedance spectroscopy (EPIS) is an emerging tool for the diagnosis of polymer electrolyte membrane fuel cells (PEMFC). It is based on analyzing the frequency response of the cell voltage with respect to an excitation of the gas-phase pressure. Several experimental studies in the past decade have shown the complexity of EPIS signals, and so far there is no agreement on the interpretation of EPIS features. The present study contributes to shed light into the physicochemical origin of EPIS features, by using a combination of pseudo-two-dimensional modeling and analytical interpretation. Using static simulations, the contributions of cathode equilibrium potential, cathode overpotential, and membrane resistance on the quasi-static EPIS response are quantified. Using model reduction, the EPIS responses of individual dynamic processes are predicted and compared to the response of the full model. We show that the EPIS signal of the PEMFC studied here is dominated by the humidifier. The signal is further analyzed by using transfer functions between various internal cell states and the outlet pressure excitation. We show that the EPIS response of the humidifier is caused by an oscillating oxygen molar fraction due to an oscillating mass flow rate.
In this paper, the J-integral is derived for temperature-dependent elastic–plastic materials described by incremental plasticity. It is implemented using the equivalent domain integral method for assessment of three-dimensional cracks based on results of finite-element calculations. The J-integral considers contributions from inhomogeneous temperature fields and temperature-dependent elastic and plastic material properties as well as from gradients in the plastic strains and the hardening variables. Different energy densities are considered, the Helmholtz free energy and the stress-working density, providing a physical meaning of the J-integral as a fracture criteria for crack growth. Results obtained for a plate with two different crack configurations each loaded by a cool-down thermal shock show domain-independence of the incremental J-integral for different energy densities even for high temperature gradients and significant temperature-dependence of the yield stress and the hardening exponent in the presence of large scale yielding. Hence, the derived J-integral is an appropriate parameter for the assessment of cracks in thermomechanically loaded components.
Building energy management systems (BEMSs), dedicated to sustainable buildings, may have additional duties, such as hosting efficient energy management systems (EMSs) algorithms. This duty can become crucial when operating renewable energy sources (RES) and eventual electric energy storage systems (ESSs). Sophisticated EMS approaches that aim to manage RES and ESSs in real time may need high computing capabilities that BEMSs typically cannot provide. This article addresses and validates a fuzzy logic-based EMS for the optimal management of photovoltaic (PV) systems with lead-acid ESSs using an edge computing technology. The proposed method is tested on a real smart grid prototype in comparison with a classical rule-based EMS for different weather conditions. The goal is to investigate the efficacy of islanding the building local network as a control command, along with ESS power control. The results show the implementation feasibility and performance of the fuzzy algorithm in the optimal management of ESSs in both operation modes: grid-connected and islanded modes.
Enzyme‐assisted HPTLC method for the simultaneous analysis of inositol phosphates and phosphate
(2023)
Background
The analysis of myo‐inositol phosphates (InsPx) released by phytases during phytic acid degradation is challenging and time‐consuming, particularly in terms of sample preparation, isomer separation, and detection. However, a fast and robust analysis method is crucial when screening for phytases during protein engineering approaches, which result in a large number of samples, to ensure reliable identification of promising novel enzymes or target variants with improved characteristics, for example, pH range, thermal stability, and phosphate release kinetics.
Results
The simultaneous analysis of several InsPx (InsP1‐InsP4 and InsP5 + 6) as well as free phosphate was established on cellulose HPTLC plates using a buffered mobile phase. Inositol phosphates were subsequently stained using a novel enzyme‐assisted staining procedure. Immobilized InsPx were hydrolyzed by a phytase solution of Quantum® Blueliquid 5G followed by a molybdate reagent derivatization. Resulting blue zones were captured by DAD scan. The method shows good repeatability (intra‐day and intra‐lab) with maximum deviations of the Rf value of 0.01. The HPTLC method was applied to three commercially available phytases at two pH levels relevant to the gastrointestinal tract of poultry (pH 5.5 and pH 3.6) to observe their phytate degradation pattern and thus visualize their InsPx fingerprint.
Conclusion
This HPTLC method presents a semi‐high‐throughput analysis for the simultaneous analysis of phytic acid and the resulting lower inositol phosphates after its enzymatic hydrolysis and is also an effective tool to visualize the InsPx fingerprints and possible accumulations of inositol phosphates.
Over the last few decades, several grid coupling techniques for hierarchically refined Cartesian grids have been developed to provide the possibility of varying mesh resolution in lattice Boltzmann methods. The proposed schemes can be roughly categorized based on the individual grid transition interface layout they are adapted to, namely cell-vertex or cell-centered approaches, as well as a combination of both. It stands to reason that the specific properties of each of these grid-coupling algorithms influence the stability and accuracy of the numerical scheme. Consequently, this naturally leads to a curiosity regarding the extent to which this is the case. The present study compares three established grid-coupling techniques regarding their stability ranges by conducting a series of numerical experiments for a square duct flow, including various collision models. Furthermore the hybrid-recursive regularized collision model, originally introduced for cell-vertex algorithms with co-located coarse and fine grid nodes, has been adapted to cell-centered and combined methods.
In this paper, the time- and temperature-dependent cyclic ratchetting plasticity of the nickel-based alloy IN100 is experimentally investigated in strain-controlled experiments in the temperature range from 300 °C to 1050 °C. To this end, uniaxial material tests are performed with complex loading histories designed to activate phenomena as strain rate dependency, stress relaxation as well as the Bauschinger effect, cyclic hardening and softening, ratchetting and recovery from hardening. Plasticity models with different levels of complexity are presented that consider these phenomena, and a strategy is derived to determine the multitude of temperature-dependent material properties of the models in a step-by-step procedure based on sub-sets of experimental data of isothermal experiments. The models and the material properties are validated based on the results of non-isothermal experiments. A good description of the time- and temperature-dependent cyclic ratchetting plasticity of IN100 is obtained for isothermal as well as non-isothermal loading with models including ratchetting terms in the kinematic hardening law and the material properties obtained with the proposed strategy.
Relationships between External, Wearable Sensor-Based, and Internal Parameters: A Systematic Review
(2023)
Micro electro-mechanical systems (MEMS) are used to record training and match play of intermittent team sport athletes. Paired with estimates of internal responses or adaptations to exercise, practitioners gain insight into players’ dose–response relationship which facilitates the prescription of the training stimuli to optimize performance, prevent injuries, and to guide rehabilitation processes. A systematic review on the relationship between external, wearable-based, and internal parameters in team sport athletes, compliant with the PRISMA guidelines, was conducted. The literature research was performed from earliest record to 1 September 2020 using the databases PubMed, Web of Science, CINAHL, and SportDISCUS. A total of 66 full-text articles were reviewed encompassing 1541 athletes. About 109 different relationships between variables have been reviewed. The most investigated relationship across sports was found between (session) rating of perceived exertion ((session-)RPE) and PlayerLoad™ (PL) with, predominantly, moderate to strong associations (r = 0.49–0.84). Relationships between internal parameters and highly dynamic, anaerobic movements were heterogenous. Relationships between average heart rate (HR), Edward’s and Banister’s training impulse (TRIMP) seem to be reflected in parameters of overall activity such as PL and TD for running-intensive team sports. PL may further be suitable to estimate the overall subjective perception. To identify high fine-structured loading—relative to a certain type of sport—more specific measures and devices are needed. Individualization of parameters could be helpful to enhance practicality.
In this paper, a temperature-dependent viscoplasticity model is presented that describes thermal and cyclic softening of the hot work steel X38CrMoV5-3 under thermomechanical fatigue loading. The model describes the softening state of the material by evolution equations, the material properties of which can be determined on the basis of a defined experimental program. A kinetic model is employed to capture the effect of coarsening carbides and a new isotropic cyclic softening model is developed that takes history effects during thermomechanical loadings into account. The temperature-dependent material properties of the viscoplasticity model are determined on the basis of experimental data measured in isothermal and thermomechanical fatigue tests for the material X38CrMoV5-3 in the temperature range between 20 and 650 ∘C. The comparison of the model and an existing model for isotropic softening shows an improved description of the softening behavior under thermomechanical fatigue loading. A good overall description of the experimental data is possible with the presented viscoplasticity model, so that it is suited for the assessment of operating loads of hot forging tools.
Running stability is the ability to withstand naturally occurring minor perturbations during running. It is susceptible to external and internal running conditions such as footwear or fatigue. However, both its reliable measurability and the extent to which laboratory measurements reflect outdoor running remain unclear. This study aimed to evaluate the intra- and inter-day reliability of the running stability as well as the comparability of different laboratory and outdoor conditions. Competitive runners completed runs on a motorized treadmill in a research laboratory and overground both indoors and outdoors. Running stability was determined as the maximum short-term divergence exponent from the raw gyroscope signals of wearable sensors mounted to four different body locations (sternum, sacrum, tibia, and foot). Sacrum sensor measurements demonstrated the highest reliabilities (good to excellent; ICC = 0.85 to 0.91), while those of the tibia measurements showed the lowest (moderate to good; ICC = 0.55 to 0.89). Treadmill measurements depicted systematically lower values than both overground conditions for all sensor locations (relative bias = -9.8% to -2.9%). The two overground conditions, however, showed high agreement (relative bias = -0.3% to 0.5%; relative limits of agreement = 9.2% to 15.4%). Our results imply moderate to excellent reliability for both overground and treadmill running, which is the foundation of further research on running stability.