Zero-dimensional Model Research Articles

Simulation and Application of Water Environment in Highly Urbanized Areas: A Case Study in Taihu Lake Basin

In the wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model’s reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed.

Particulate Matter Emission and Air Pollution Reduction by Applying Variable Systems in Tribologically Optimized Diesel Engines for Vehicles in Road Traffic

Regardless of the increasingly intensive application of vehicles with electric drives, internal combustion engines are still dominant as power units of mobile systems in various sectors of the economy. In order to reduce the emission of exhaust gases and satisfy legal regulations, as a temporary solution, hybrid drives with optimized internal combustion engines and their associated systems are increasingly being used. Application of the variable compression ratio and diesel fuel injection timing, as well as the tribological optimization of parts, contribute to the reduction in fuel consumption, partly due to the reduction in mechanical losses, which, according to test results, also results in the reduction in emissions. This manuscript presents the results of diesel engine testing on a test bench in laboratory conditions at different operating modes (compression ratio, fuel injection timing, engine speed, and load), which were processed using a zero-dimensional model of the combustion process. The test results should contribute to the optimization of the combustion process from the aspect of minimal particulate matter emission. As a special contribution, the results of tribological tests of materials for strengthening the sliding surface of the aluminum alloy piston and cylinder of the internal combustion engine and air compressors, which were obtained using a tribometer, are presented. In this way, tribological optimization should also contribute to the reduction in particulate matter emissions due to the reduction in fuel consumption, and thus emissions due to the reduction in friction, as well as the recorded reduction in the wear of materials that are in sliding contact. In this way, it contributes to the reduction in harmful gases in the air.

Airmass history, night-time particulate organonitrates, and meteorology impact urban SOA formation rate

With respect to air quality, the San Antonio metropolitan area, with a population of 1.45 million and the second largest city in Texas, has been designated as non-attainment by the United States Environmental Protection Agency in recent years. Despite the operation of multiple stationary air quality monitoring sites by the Texas Commission on Environmental Quality, the in-situ measurements of submicron aerosol and its precursors in the region is limited. To better understand the formation of secondary organic aerosol (SOA) in the San Antonio urban core, we conducted observations of a range of trace gases, volatile organic compounds, submicron aerosol, and meteorological parameters in May 2017. Data from a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) show that organic aerosol (OA) was the dominant component of non-refractory submicron particulate matter (average±1σ, 55 ± 32 %, 5.86 ± 3.40 μg m−3), followed by sulfate (33 ± 23 %, 3.52 ± 2.47 μg m−3). Aerosol liquid water contents predicted by ISORROPIA-II greatly increase from Continental to Oceanic airmass history scenarios, while inorganic aerosol pH remains very acidic. Positive matrix factorization (PMF) analysis of the OA mass spectra indicates that two classes of oxygenated OA (less and more-oxidized OOA, LO and MO) together constituted the bulk of OA mass during the study period (MO-OOA: 44 ± 39 %, 2.35 ± 2.07 μg m−3; LO-OOA: 42 ± 34 %, 2.22 ± 1.77 μg m−3), while the fraction of hydrocarbon-like OA was limited (13 ± 21 %, 0.71 ± 1.11 μg m−3). Using in-situ meteorological data and location-specific empirical coefficients, a zero-dimensional model that utilized PMF factors as proxies to calculate the net rate of formation of types of SOA has been developed; similar calculations were used to estimate the formation rate of particulate organonitrates (pON). The results from the model reveal the importance of pON formation in LO-OOA formation overnight and the influence of temperature and photochemistry during the day. The relationships between local atmospheric factors and the net rate of formation of MO-OOA are not statistically significant. These results emphasize how HR-ToF-AMS-PMF factors could be incorporated into chemistry modeling to evaluate quantitatively the rates of formation of SOA and reveal diurnal differences in SOA formation pathways in a major urban area in southern United States.

Advancing Reservoir Performance Optimization through UserFriendly Excel VBA Software Development

This study addresses the pressing demand for streamlined field performance analysis within oil and natural gas development, which currently necessitates substantial expertise and time investment. The principal aim involves developing a user-friendly software tool dedicated to optimizing reservoir rendition. Leveraging the Havlena and Odeh material balance straight line equation form, this tool integrates a zero-dimensional reservoir model with Decline Curve Analysis. The implementation of this user-friendly software enables achievable material balance optimization by aligning cumulative produced fluid with historical production data, akin to the widely acknowledged concept of history matching in material balance analysis. This accomplishment not only facilitates further endeavors like pressure simulation and forecasting but also augments the comprehension of reservoir dynamics. The analysis incorporated three datasets: one modeled from L.P. Dake's textbook and two drawn from real-life reservoirs in the Niger Delta. Assessment of estimated water influx and cumulative oil production indicated minimal discrepancies between Np Real and Np model for these reservoirs. Consequently, material balance history matching for these reservoirs seems feasible. Achieving reservoir rendition optimization involved a Microsoft Excel VBA code consisting of two hundred and thirty-five (235) lines, meticulously designed to replicate MBAL functionality. The software demonstrated congruent outcomes with MBAL, affirming its reliability for history matching and enhancing reservoir performance. We strongly advocate the utilization of this software for optimizing reservoir performance across diverse global regions. Its capacity to streamline field analysis could significantly benefit the oil and natural gas industry.

Argon metastable density and temperature of a 94 GHz microplasma

Laser diode absorption spectroscopy is used to experimentally measure Ar(1s5) metastable density and translational gas temperature within a 94 GHz microplasma. A square two-dimensional photonic crystal (PhC) at this resonance frequency serves to ignite and sustain the plasma from 20 to 200 Torr (2.7 × 103–2.7 × 104 Pa) by using millimeter wave power from 300 to 1000 mW. Metastable density within the plasma is estimated from the absorption line shape of the laser traversing the PhC. The metastable density reaches an order of 1019 m−3 at lower pressure and decreases as pressure increases. From the Lorentzian line shape of the absorption profile at 811.53 nm, the gas temperature is extracted and found to increase from 500 K at 20 Torr to 1300 K at 200 Torr. These data are analyzed and compared with a zero-dimensional plasma model and with previous experimental plasma results at 43 GHz.

A modular framework for implicit 3D–0D coupling in cardiac mechanics

In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and efficient technique is to use an electrical circuit analogy, known as a lumped parameter network or zero-dimensional (0D) fluid model, to represent blood flow throughout the cardiovascular system. Due to the strong physical interaction between the heart and the blood circulation, developing accurate and efficient numerical coupling methods remains an active area of research. In this work, we present a modular framework for implicitly coupling three-dimensional (3D) finite element simulations of cardiac mechanics to 0D models of blood circulation. The framework is modular in that the circulation model can be modified independently of the 3D finite element solver, and vice versa. The numerical scheme builds upon a previous work that combines 3D blood flow models with 0D circulation models (3D fluid–0D fluid). Here, we extend it to couple 3D cardiac tissue mechanics models with 0D circulation models (3D structure–0D fluid), showing that both mathematical problems can be solved within a unified coupling scheme. The effectiveness, temporal convergence, and computational cost of the algorithm are assessed through multiple examples relevant to the cardiovascular modeling community. Importantly, in an idealized left ventricle example, we show that the coupled model yields physiological pressure–volume loops and naturally recapitulates the isovolumic contraction and relaxation phases of the cardiac cycle without any additional numerical techniques. Furthermore, we provide a new derivation of the scheme inspired by the Approximate Newton Method of Chan (1985), explaining how the proposed numerical scheme combines the stability of monolithic approaches with the modularity and flexibility of partitioned approaches.

A hybrid plasma model for Cr thin film deposition by deep oscillation magnetron sputtering

A time-dependent hybrid plasma model composed of a zero-dimensional global model and a two-dimensional fluid model is proposed for simulation of plasma chemistry and transportation of plasma during Cr thin film deposition by deep oscillation magnetron sputtering (DOMS). The global model deals with plasma reactions in the ionization region near the target with discharge voltage and current waveforms as inputs. The temporal plasma characteristics calculated by the global model are utilized as a boundary condition for the two-dimensional fluid model to simulate high-density plasma transportation in the diffusion region through the entire macropulse period. The full momentum equation taking inertia force into consideration is applied for ion momentum conservation in the fluid model instead of using the drift-diffusion approximation, which ensures validity of the simulation for low-pressure plasmas. The deposition flux as well as the kinetic and potential energy fluxes transferred to the growing films are calculated by the hybrid model. Microstructure evolution of the DOMS deposited Cr thin films from zone I to zone T is attributed to the growing kinetic and potential energies as the charging voltage increases according to the structure zone diagram. The deposition rate loss in DOMS is explained by the back attraction effect, sputtering yield effect, and densification of the films.

A comprehensive thermal analysis of icemaking process inside a domestic freezer: Theoretical, numerical and experimental analyses

Automatic icemakers are integrated into refrigerators to ensure a consistent ice supply and improve energy efficiency. Despite these advantages, a thorough investigation of the automatic icemaking process in domestic refrigerator-freezers is lacking in the literature. This study aims at assessing the performance of automatic icemaking process in a domestic freezer through detailed theoretical, numerical and experimental analyses. A simplistic zero-dimensional transient energy balance model is developed to investigate the heat transfer during different stages of the water solidification process. The convective heat transfer coefficient calculated from the theoretical analysis is used to inform the numerical model. A three-dimensional transient model is proposed to predict the temperature and density variation inside the ice cube modelled as a pyramid. The free surface flow is modelled using volume of fluid method, while enthalpy-porosity method is employed for the water freezing process. The results show a non-uniform temperature distribution throughout the solidification process and that the temperature of the outer frozen layers keeps decreasing with the solidification time. Experiments are conducted to measure the temperature variation of the ice cube. It is shown that the icemaking process is accelerated by around 18 % when the ice-removal temperature is set at −8°C instead of −12 °C, which is a conventional set temperature for ice remover in current domestic freezers.

Modeling nitrogen species from ammonia reciprocating engine combustion in temperature-equivalence ratio space

This paper explores nitrogen species formation in temperature (T)-equivalence ratio (ϕ) space under internal combustion engine-relevant conditions using zero-dimensional modeling. The analysis reveals that N2O and NO are formed in a much larger region of ϕ-T space than in hydrocarbon combustion due to fuel chemical pathways. N2O is formed over a large range of ϕ, primarily in low temperature regions that have significant levels of unburned NH3. NO is formed over a large, high temperature, lean region. Further analysis shows that even when mixing burned gas with unburned NH3 from engine crevices, N2O is reduced to low levels in the expansion stroke after initially increasing due to the thermal de-NOx mechanism. This indicates that N2O emissions measured from premixed engine combustion are likely from quenching near cold surfaces.

Coupling of high-temperature proton exchange membrane fuel cells with methanol steam reforming: Modeling and simulation for an integrated coupled for power generation system

This study established a zero-dimensional numerical model integrating methanol steam reforming (MSR) and high-temperature proton exchange membrane fuel cells (HT-PEMFC), systematically investigating the effects of parameters such as steam-methanol (S/C) ratio, reformer reaction temperature, methanol catalytic combustion ratio, fuel cell number, and anode stoichiometry on the thermal, mass, electrical, and efficiency performance parameters of the integrated system. The results confirmed that the integrated system can achieve thermal self-sustained operation without the need for additional heat from methanol catalytic combustion. Improved insulation quality enables the attainment of thermal self-sufficiency at lower operating conditions. The molar ratio of CO in the reformate increases with a decrease in the S/C ratio and an increase in the reformer reaction temperature. The system achieves maximum output power and efficiency when S/C equals 1.25 and the reformer temperature is 513 K, with increases of 8.6 % and 37.1 %, respectively. The system efficiency is highly sensitive to the anode stoichiometry of the fuel cell, showing an 11.7 % improvement as the stoichiometry decreases from 2.0 to 1.2. Based on these results, three improvement measures were proposed to enhance the performance of MSR and HT-PEMFC integrated systems: improving system insulation to lower thermal self-sufficiency conditions, optimizing the stoichiometry of the bipolar plates for significant efficiency improvement, and selecting appropriate operating parameters for system components to enhance overall performance. This study quantitatively demonstrates the potential of these measures to improve system performance, providing valuable insights for the design and optimization of integrated systems.

Modelagem integrada de qualidade e quantidade para gestão de recursos hídricos: estudo de caso na Bacia do Alto Paranapanema

ABSTRACT This study introduces an integrated model for water resources planning and management that accounts for both the quantity and quality of water in watersheds and reservoirs. Therefore, it provides a comprehensive approach for better understanding and assessing water systems. The model facilitates analyses of the spatial and temporal dynamics of hydrological processes, pollutant transport, and the behavior of rivers and reservoirs. The study evaluated pollutant load transport in the Upper Paranapanema Basin by applying the Soil Moisture Accounting Procedure (SMAP) model, Muskingum method, Streeter-Phelps buildup/washoff model, and zero-dimensional (0D) models to estimate inflows to the Jurumirim reservoir. A Python-based public library was developed to model all hydrological processes. The model calibration yielded a NSE, KGE, PBIAS and RMSE result of 0.746, 0.778, 6.5% and 73.3 m 3 s − 1, respectively. Indicating a robust simulation that attests to the versatility and reliability of the proposed approach. The methodology outlined in this research enables comprehensive water quality simulation at basin scale, thereby serving as a tool for understanding water quantity and quality dynamics and support decision-making regarding water resource planning and management.

Spectral analysis and kinetic modeling of radioluminescence in air and nitrogen.

In this article we present a quantitative analysis of the second positive system of molecular nitrogen and the first negative system of the molecular nitrogen cation excited in the presence of ionizing radiation. Optical emission spectra of atmospheric air and nitrogen surrounding 210Po sources were measured from 250 to 400 nm. Multi-Boltzmann and non-Boltzmann vibrational distribution spectral models were used to determine the vibrational temperature and vibrational distribution function of the emitting N2(C3Πu) and N2+(B2Σ+u) states. A zero-dimensional kinetic model, based on the electron energy distribution function (EEDF) and steady-state excitation and de-excitation of N2(X1Σ+g), N2+(B2Σ+u), N2+(X2Σ+g), N4+, O2+, and N2(C3Πu, v), was developed for the prediction of the relative spectral intensity of both the N2+(B2Σ+u → X2Σ+g) emission band and the vibrational bands of N2(C3Πu → B3Πg) for comparison with the experimental data.

Impact of temperature-dependent non-PAN peroxynitrate formation, RO2NO2, on nighttime atmospheric chemistry.

The formation of peroxynitrates (RO2NO2) from the reaction of peroxy radicals (RO2) and nitrogen dioxide (NO2) and their subsequent redissociation are typically not included in chemical mechanisms. This is often done to save computational time as the assumption is that the equilibrium is strongly towards the RO2 + NO2 reaction for most conditions. Exceptions are the reactions of the methyl peroxy radical due to its abundance in the atmosphere and of acyl-RO2 radicals due to the long lifetime of peroxyacyl nitrates RO2NO2 (PANs). In this study, the nighttime oxidation of cis-2-butene and trans-2-hexene in the presence of NO2 is investigated in the atmospheric simulation chamber SAPHIR, Forschungszentrum Jülich, Germany, at atmospherically-relevant conditions at different temperatures (≈276 K, ≈293 K, ≈305 K). Measured concentrations of peroxy and hydroperoxy radicals as well as other trace gases (ozone, NO2, volatile organic compounds) are compared to state-of-the-art zero-dimensional box model calculations. Good model-measurement agreement can only be achieved when reversible RO2 + NO2 reactions are included for all RO2 species using literature values available from the latest SAR by [Jenkin et al., Atmos. Chem. Phys., 2019, 19, 7691]. The good agreement observed gives confidence that the SAR, derived originally for aliphatic RO2, can be applied to a large range of substituted RO2 radicals, simplifying generalised implementation in chemical models. RO2NO2 concentrations from non-acyl RO2 radicals of up to 2 × 10 cm-3 are predicted at 276 K, impacting effectively the kinetics of RO2 radicals. Under these conditions, peroxy radicals are slowly regenerated downwind of the pollution source and may be lost in the atmosphere through deposition of RO2NO2. Based on this study, 60% of RO2 radicals would be stored as RO2NO2 at a temperature of 10 °C and in the presence of a few ppbv of NO2. The fraction increases further at colder temperatures and/or higher NO2 mixing ratios. This does not only affect the expected concentrations of RO2 radicals but, as the peroxynitrates can react with OH radicals or photolyse, they could comprise a net sink for RO2 radicals as well as increase the production of NOx (= NO + NO2) in different locations depending on their lifetime. Omitting this chemistry from the kinetic model can lead to misinterpreted product formation and may prevent reconciling observations and model predictions.

THEORETICAL INVESTIGATION ON COMBUSTION HETEROGENEITY IN INTERIOR BALLISTICS OF MORTAR USING POPULATION BALANCE EQUATION

The ever-rolling progress of weapon systems has proven to demand an increase in precision in the models to be able to achieve further improvements. In the field of interior ballistics, one of the elements that remains excluded from most models is the combustion heterogeneity due to non-equilibrium of pressure. This paper presents a zero-dimensional model of a mortar. It includes two chambers: the combustion chamber and the cartridge with combustion heterogeneity occurring between these two chambers. The model adapted to this kind of problem is the population balance equation (PBE). A successful attempt to solve the PBE numerically in this case, using the class method, is presented in this work to theoretically address the quantification of the impact of combustion heterogeneities too often ignored.

A PHYSICAL MODEL FOR THE PREDICTION OF ALUMINUM OXIDE RESIDUES

This work proposes a new model to estimate the size of oxide residues produced during the combustion of aluminum. Such large oxide residues contribute to the two-phase loss performance in solid rocket motors. The model includes two physical mechanisms: deposition of oxide smoke from the surrounding flame and oxide creation on aluminum surface by heterogeneous reactions. Parametric numerical simulations at the aluminum droplet scale are performed to estimate the rate of deposition and surface production, in order to feed a zero-dimensional model of oxide lobe growth and final oxide residue. Results are in line with available measurements with an oxide residue-to-aluminum size ratio in the range 0.5 ~ 0.8, depending on conditions. The model suggests that surface reactions are important for low pressures and small particles, while deposition prevails otherwise.

(Invited) Understanding Capacity Fade Behavior in Aqueous Organic Redox Flow Batteries Via Zero-Dimensional Models and High-Throughput Cell Cycling

Aqueous Organic Redox Flow Batteries (AORFBs) have emerged as promising and potentially disruptive technologies for the storage of electrical energy from intermittent renewable sources for use over long discharge durations when the sun isn’t shining and the wind isn’t blowing. AORFBs could become preferred over Li-ion batteries for grid-scale stationary storage due to their potentially low-cost active materials made of Earth-abundant elements, their inherent non-flammability, and the intrinsic decoupling of energy and power capacities in the flow battery design. Our group has demonstrated that calendar life, rather than cycle life, limits molecular lifetimes in AORFBs due to various molecular instabilities that lead to side reactions, thus inhibiting performance [1]. To accurately determine molecular fade rates, we utilize potentiostatic cycling to avoid artifacts caused by drifts in internal resistance and employ volumetrically unbalanced compositionally symmetric cell configurations to distinguish molecular fade from membrane crossover or the two sides drifting out of balance.We have developed a high-throughput setup for AORFBs, capable of cycling cells at elevated temperatures, providing a new dimension in the flow battery characterization space to explore multiple cell parameters simultaneously. The recent incorporation of the decay of active material into zero-dimensional cell-cycling models for AORFBs [2,3] allows for exploration of the causes of various trends seen in flow cell temporal capacity behavior. Complemented by zero-dimensional modelling, we explore temporal capacity evolution in symmetric cells driven by different capacity fade mechanisms such as active species degradation [4], self-discharge [5], and membrane crossover. Collectively, these results highlight the relevance of electrochemical techniques to understand molecular degradation in AORFBs and expedite the screening process of candidate molecules for long lifetime AORFBs, which may enable massive grid penetration of intermittent renewable energy.[1] M.-A. Goulet and M. J. Aziz, “Flow Battery Molecular Reactant Stability Determined by Symmetric Cell Cycling Methods,” Journal of The Electrochemical Society, 165, A1466 (2018).[2] S. Modak and D. G. Kwabi, “A Zero-Dimensional Model for Electrochemical Behavior and Capacity Retention in Organic Flow Cells,” Journal of the Electrochemical Society, 168, 080528 (2021).[3] B. J. Neyhouse, J. Lee, F. R. Brushett, “Connecting Material Properties and Redox Flow Cell Cycling Performance through Zero-Dimensional Models” Journal of The Electrochemical Society, 169, 090503 (2022).[4] D. G. Kwabi, Y. Ji, M. J. Aziz, “Electrolyte Lifetime in Aqueous Organic Redox Flow Batteries: A Critical Review,” Chemical Reviews, 120, 6467 (2020).[5] E. M. Fell, D. De Porcellinis, Y. Jing, V. Gutierrez-Venegas, R. G. Gordon, S. Granados-Focil, M. J. Aziz, “Long-term stability of ferri-/ferrocyanide as an electroactive component for redox flow battery applications: On the origin of apparent capacity fade,” ChemRxiv (2022). https://chemrxiv.org/engage/chemrxiv/article-details/62913087f89e5d4e6ee8828d

Quantifying and valuing irrigation in energy and water limited agroecosystems

Agriculture in regions with limited water availability is possible because of irrigation. Irrigated croplands are expanding, and irrigation water demand is increasing. Nevertheless, there is a limited understanding of how much water is consumed for irrigation and how effective irrigation increases crop productivity in various climates. In this study, we aim to understand how irrigation water affects crop productivity in different climates. To achieve this goal, we developed a simple approach to quantify irrigation quantities from SMAP satellite soil moisture observations based on a zero-dimensional bucket-type hydrology model. The central assumption is that irrigation quantities can be estimated from the gap between the modeled and observed soil moisture by iteratively providing irrigation as a model input until the soil moisture simulations agree well with the observations. We then used the estimated amount of irrigation to simulate water, energy, and carbon fluxes at two agricultural sites on the west coast of the US: one that was water-limited (Central Valley, CA) and one that was energy-limited (Eugene, OR). An agroecosystem model, AgroIBIS-VSF, was used to conduct simulations. To verify our simulations, we used data from two AmeriFlux Eddy covariance towers at each site. We found that incorporating estimated irrigation amounts into our simulations improved the accuracy of energy balance components and soil moisture predictions, reducing the root-mean-square error of soil moisture predictions by up to 22%. We also discovered that the irrigation value, in terms of increased productivity of actual irrigation water used, is more than five times more valuable at the energy-limited site than at the water-limited site. Soil hydraulic properties have a strong influence on irrigation water valuation. Our study highlights the potential of satellite soil moisture observations to improve our understanding of water productivity in different climates. By better understanding the efficiency of resources used for crop production, we can ensure the sustainability and resilience of agricultural systems, leading to better management practices.

INCHEM-Py v1.2: a community box model for indoor air chemistry

Abstract. The Indoor CHEMical model in Python, INCHEM-Py, is an open-source and accessible box model for the simulation of the indoor atmosphere and is a refactor (rewrite of source code) and significant development of the INdoor Detailed Chemical Model (INDCM). INCHEM-Py creates and solves a system of coupled ordinary differential equations that include gas-phase chemistry, surface deposition, indoor–outdoor air change, indoor photolysis processes and gas-to-particle partitioning for three common terpenes. It is optimised for ease of installation and simple modification for inexperienced users, while also providing unfettered access to customise the physical and chemical processes for more advanced users. A detailed user manual is included with the model and updated with each version release. In this paper, INCHEM-Py v1.2 is introduced, and the modelled processes are described in detail, with benchmarking between simulated data and published experimental results presented, alongside discussion of the parameters and assumptions used. It is shown that INCHEM-Py achieves excellent agreement with measurements from an experimental campaign which investigate the effects of different surfaces on the concentrations of different indoor air pollutants. In addition, INCHEM-Py shows closer agreement to experimental data than INDCM. This is due to the increased functionality of INCHEM-Py to model additional processes, such as deposition-induced surface emissions. A comparative analysis with a similar zero-dimensional model, AtChem2, verifies the solution of the gas-phase chemistry. Published community use cases of INCHEM-Py are also presented to show the variety of applications for which this model is valuable to further our understanding of indoor air chemistry.

Design, modeling, and analysis of a PV/T and PEM fuel cell based hybrid energy system for an off-grid house

Net-zero emission targets have imposed the transition to clean and efficient energy technologies, considering the problems arising from the discontinuous and variable nature of renewable energy resources. Integrated energy systems based on solar and hydrogen energy are becoming essential to obtain uninterrupted power, especially for off-grid applications. This study focuses on the design, modeling, and evaluation of such a system that meets the energy consumption of a residence in Türkiye. The framework basically consists of photovoltaic/thermal panels (PV/Ts), batteries, a PEM electrolyzer (PEM-El), hydrogen (H2) storage tanks, and PEM fuel cells (PEM-FC). A zero-dimensional mathematical model was developed for each of the components of the system. Yearly analyses were conducted with a new control strategy based on power balancing, and dynamic variations in power generated by the PV/T panel, the SOCs of batteries, the power consumption of the PEM-El, the power generated by the PEM-FC and the amount of hydrogen in the tank were examined. The results showed that the electricity requirement of a 100 m2 house can be met continuously for a year with 20 PV/T panels (total area of 32.71 m2) with a total capacity of 62 kW, 8 batteries with a total capacity of 192 kWh, and 7 H2 storage tanks with a total capacity of 29.4 kg. It was also shown that the electricity needs of the house is met by stored hydrogen between December and April. Furthermore, the hybrid system’s economic evaluation was carried out and the investment cost of the system was calculated.

Toward tiny high-power-density thermoelectric harvesters

Thermoelectric (TE) generators (TEGs) have recently attracted significant attention for harvesting ubiquitous heat energy to power industrial sensor nodes or wearable and implantable electronics. Such applications require that a small, fitted heat sink be incorporated into a tiny harvester to ensure conformal deployment and ease of use. Since the small heat sink will exhibit very poor heat rejection performance, the optimal structural design of the TEG device and the proper selection of its constituent TE materials are extremely important to ensure that sufficient electric power is provided to the connected post-stage circuits. Regrettably, the traditional forward design strategies, i.e., material-to-device and device-to-harvester, are often disconnected from one another and fail to form a complete chain, thereby presenting a fundamental challenge in achieving ultrahigh-power-density harvesters. Here we present a zero-dimensional model for a tiny harvester to establish a set of new metrics (not limited to the figure of merit zT) that can be used to determine the optimal TE material and to directly deduce the optimal configuration of the TEG for guaranteeing the maximum output power at various load conditions, making backward design strategy possible. Two tiny harvesters are accordingly fabricated and exhibit areal power densities 52 and 94 times that of a harvester incorporating a commercial TEG, with identical amounts of TE material used for each.