Investigations of safety issues related to the design and operation of high-pressure proton exchange membrane (PEM) water electrolysers have until now mainly focused on the electrolyser stack. The ...present study focuses on the risk of explosive mixture formation in the water recovery system, which is part of the balance of plant in water electrolysers. After a major electrolyser company experienced an unexpected detonation in their system, we analysed their process design as a base case: a low-pressure buffer tank where anodic and cathodic water is mixed with make-up deionised water poses a safety risk because an explosive gas mixture is likely to form there, resulting in severe accidents. Several retrofit options are explored using dynamic and steady-state simulation models: these options are then evaluated based on their effects on safety, general economics and operation of the plant, in addition to ease of retrofit. The results show that preventing the formation of explosive gas mixtures in the water recovery system is achievable in several ways, such as avoiding recycling cathodic water altogether, stripping it of hydrogen, flushing buffer tanks with nitrogen or oxygen, rearranging the balance of plant appropriately, or changing the control algorithms of the system.
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•Common electrolyser plant designs can generate explosive mixtures in the balance of plant.•Such designs have led to unwanted accidents with potential for escalation.•The explosion threshold can be reached in less than 10 min from plant startup.•There are several retrofit options to ensure safe operation.
Bisphenol A (BPA) is one of the best studied industrial chemicals in terms of exposure, toxicity, and toxicokinetics. This renders it an ideal candidate to exploit the recent advancements in ...physiologically based pharmacokinetic (PBPK) modelling to support risk assessment of BPA specifically, and of other consumer-relevant hazardous chemicals in general. Using the exposure from thermal paper as a case scenario, this study employed the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) model available in the Simcyp® Simulator to simulate the dermal toxicokinetics of BPA at local and systemic levels. Sensitivity analysis helped to identify physicochemical and physiological factors influencing the systemic exposure to BPA. The iterative modelling process was as follows: (i) development of compound files for BPA and its conjugates, (ii) setting-up of a PBPK model for intravenous administration, (iii) extension for oral administration, and (iv) extension for exposure via skin (i.e., hand) contact. A toxicokinetic study involving hand contact to BPA-containing paper was used for model refinement. Cumulative urinary excretion of total BPA had to be employed for dose reconstruction. PBPK model performance was verified using the observed serum BPA concentrations. The predicted distribution across the skin compartments revealed a depot of BPA in the stratum corneum (SC). These findings shed light on the role of the SC to act as temporary reservoir for lipophilic chemicals prior to systemic absorption, which inter alia is relevant for the interpretation of human biomonitoring data and for establishing the relationship between external and internal measures of exposure.
•Pharmacokinetic modelling of dermal absorption of bisphenol A (BPA) from thermal paper.•Physiologically based kinetic modelling of dermal exposure to BPA via hand contact.•Preferential partitioning of BPA from skin surface into the stratum corneum (SC).•Delayed and long-lasting transfer of BPA from SC into systemic circulation.•The thick SC of the palms acts as temporary reservoir.
The irregular appearance of planktonic algae blooms off the coast of southern California has been a source of wonder for over a century. Although large algal blooms can have significant negative ...impacts on ecosystems and human health, a predictive understanding of these events has eluded science, and many have come to regard them as ultimately random phenomena. However, the highly nonlinear nature of ecological dynamics can give the appearance of randomness and stress traditional methods—such as model fitting or analysis of variance—to the point of breaking. The intractability of this problem from a classical linear standpoint can thus give the impression that algal blooms are fundamentally unpredictable. Here, we use an exceptional time series study of coastal phytoplankton dynamics at La Jolla, CA, with an equation-free modeling approach, to show that these phenomena are not random, but can be understood as nonlinear population dynamics forced by external stochastic drivers (so-called "stochastic chaos"). The combination of this modeling approach with an extensive dataset allows us to not only describe historical behavior and clarify existing hypotheses about the mechanisms, but also make out-of-sample predictions of recent algal blooms at La Jolla that were not included in the model development.
Abstract
The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and ...two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).
Two novel, origami-inspired, metamaterials were designed, mechanically tested, and modelled. One novel origami model was folded using a triangular based crease pattern and the other was folded using ...a rectangular based crease pattern. The origami-inspired metamaterial sheets were fabricated from polylactic acid using fused deposition additive manufacturing. Several configurations, parameterized by varying the fold angle, were mechanically tested under compression and impact loads. It was found that the specific elastic compression modulus of these novel designs was higher, ranging from 594 MPa/kg to 926 MPa/kg, than existing origami-inspired structures made based on the popular Ron-Resch design, which had specific elastic compression moduli between 15 MPa/kg to 365 MPa/kg. A finite element model further analysed the stress distribution of the core structures under compression loads. The impact testing results showed that the pattern of the tessellated cores affected the amount of impact force transferred through the samples, whereas the fold angle of the origami-inspired design had little impact on the results. The rectangular structure was shown to transfer approximately 50–75% of the force transferred by the triangular structure under impact loads.
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•Two novel, origami-inspired, tessellated patterns were designed for use as light-weight cores in sandwich structures.•Compressions tests showed that increasing fold angle improved the metamaterials’ resistance to compression loads.•The elastic compression moduli of both new designs were higher than that of existing Miura-ori and Ron Resch designs.•The ability to absorb impact force was dependant on the tessellated design pattern and independent of the origami fold angle.
Peak-current-mode (PCM) control was published first time in open literature in 1976. The observed peculiar behavior caused by the application of PCM control in a power electronic converter have ...fascinated the researchers to attempting to capture the dynamics associated to it. It is commonly assumed that the peculiar phenomena originate from the sampling process in the PCM control. A resistor is usually connected as a load, when modeling the converter dynamics and during the frequency-response measurements. The load resistor will actually dominate the frequency responses and hide the real dynamics associated to PCM control. Other measurement problems will arise from the nonmodeled circuit elements dominating, especially, the high-frequency dynamic behavior of the converters. As a consequence of these problems, the PCM models are not usually properly validated. The investigations, in this paper, show the following: 1) the PCM models have to be accurate also at the low frequencies for ensuring, for example, stable design of output-current-feedback-controlled converters; 2) the high low-frequency accuracy can be obtained only by means of duty-ratio gain becoming infinite at the mode limit; 3) the high-frequency accuracy of the PCM models can be obtained by means of different high-frequency extensions; 4) the key for the PCM modeling lies in the proper duty-ratio constraints; and 5) the high-frequency magnitude and phase behaviors are caused by the second-harmonic-mode operation of the converter due to the frequency-response-measurement injection signal. The main objective of this paper is to show that such a modeling technique, which fully matches the aforementioned criteria, has been developed already in early 1990s and later elaborated for more a general form. Validation of the dynamic models is performed by simulation, where the converter and its operational environment are perfectly known. The load-resistor effect is removed computationally for performing the complete validation. A PCM-controlled buck converter is used as an example.
Agent-based modelling has the potential to provide insight into complex energy transition dynamics. Despite a recent emphasis of research on agent-based modelling and on energy transitions, an ...overview of how the methodology may be of value to understanding transition processes is still missing from the literature. This systematic review evaluates the potential of agent-based modelling to understanding energy transitions from a social-scientific perspective, based on a set of 62 articles. Six topic areas were identified, addressing different components of the energy system: Electricity Market, Consumption Dynamics/ Consumer Behaviour, Policy and Planning, New Technologies/ Innovation, Energy System, Transitions. Distribution of articles across topic areas was indicative of a continuing interest in electricity market related enquiries, and an increasing number of studies in the realm of policy and planning. Based on the relevance of energy transition specific complexities to the choice of ABM as a methodology, four complexity categories (1–4) were identified. Indicating the degree of association between the complexity of energy transitions and ABM’s ability to address these, the categorisation revealed that 35 of the 62 studies directly linked the choice of ABM to energy transition complexities (complexity category 1) or were set in the context of energy transitions (complexity category 2). The review further showed that the greatest potential contribution of ABM to energy transition studies lies in its practical application to decision-making in policy and planning. More interdisciplinary collaboration in model development is recommended to address the discrepancy between the relevance of social factors to modelling energy transitions and the ability of the social sciences to make effective use of ABM.
AIM: Species often remain undetected at sites where they are present. However, the impact of imperfect detection on species distribution models (SDMs) is not fully appreciated. In this paper we ...evaluate the influence of imperfect detection on the calibration and discrimination capacity of SDMs. We compare the performance of three types of SDMs: (1) a technique based on presence–absence data, (2) a technique based on presence–background data, and (3) a technique based on detection/non‐detection data that accounts for imperfect detection. INNOVATION: We use simulations to evaluate the impacts of imperfect detection in SDMs. This allows us to assess model performance with respect to the true objective of the models: the estimation of species distributions. We study a range of scenarios of occupancy and detection based on ecologically plausible environmental relationships and identify the circumstances in which imperfect detection affects model calibration and discrimination. We show that imperfect detection can substantially reduce the inferential and predictive accuracy of presence–absence and presence–background methods that do not account for detectability. While calibration is always affected, the influence on discrimination depends on the relationship of detectability and environmental variables. MAIN CONCLUSIONS: The performance of a model should be assessed with respect to its objectives. Comparative studies that intend to assess the performance of an SDM by evaluating its ability to predict detections rather than presences fail to reveal the benefits of accounting for detectability. Disregarding imperfect detection can have severe consequences for SDM performance, and hence for the estimation of species distributions. To date, this issue has been largely ignored in the SDM literature. Simultaneously modelling occupancy and detection does not necessarily require a greater sampling effort, but rather that data are collected so that they are informative about detectability. We recommend that consideration of imperfect detection become standard practice for species distribution modelling.
Aim: When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is ...usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time, we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models. Innovation: In this paper we corroborate that, under a uniform distribution of the estimated probability of presence, a well-calibrated model will not attain high discrimination power and the value of the area under the curve will be 0.83. Under non-uniform distributions of the probability of presence, simulations show that a well-calibrated model can attain a broad range of discrimination values. These results illustrate that discrimination is a context-dependent property, i.e. it gives information about the performance of a certain algorithm in a certain data population. Main conclusions: In species distribution modelling, the discrimination capacity of a model is only meaningful for a certain species in a given geographic area and temporal snapshot. This is because the representativeness of the environmental domain changes with the geographical and temporal context, which unavoidably entails changes in the distribution of the probability of presence. Comparative studies that intend to generalize their results only based on the discrimination capacity of models may not be broadly extrapolated. Assessment of calibration is especially recommended when the models are intended to be transferred in time or space.
Vehicle Integrated PhotoVoltaics (VIPV) technology holds immense promise for extending the operational range of Electric Vehicles by integrating Photovoltaic cells onto vehicle surfaces. However, ...VIPV faces unique challenges coming from the dynamic nature of vehicular movement and the complex urban environment. This paper presents a comprehensive methodology for the analysis of VIPV systems, addressing these challenges. Light Detection and Ranging (LiDAR) technology provides a high-resolution point cloud to characterize urban topography and enables to analyse of the impact of urban objects on the different components of the irradiance. The proposed methodology is validated through a measurement campaign, demonstrating the accuracy of the proposed modelling. By bridging empirical data collection with computational modelling, this research provides a robust foundation for analysing VIPV systems in urban environments.
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