One-dimensional Model Research Articles

Effects of concentrated CO2 on the performance of a PBI/H3PO4 high temperature proton exchange membrane fuel cell

In this study, the impact of mimic reformate of formic acid decomposition on the anode polarization of HT-PEMFC is investigated under various operating conditions of the anode, including different concentrations of CO2, N2, CO, and humidification. Polarization curve and EIS measurements indicate that there is no significant difference (less than 5 mV when i < 0.4A/cm2) between the same concentrations of CO2 and N2 up to 75 vol%. No significant poisoning of the anode by CO2 (up to 75 vol%) has been observed, suggesting that the addition of concentrated CO2 acts more as a diluent than a poison. Upon separating the polarization effects, it is found that the oxygen reduction reaction (ORR) is a crucial step limiting the fuel cell performance, with cathodic activation losses reaching as high as 70 % at 0.8A/cm2. However, with 1 vol% CO in a H2/CO2 1/1 mixture, a significant poisoning effect on the fuel cell is observed. DRT (distribution of relaxation times) analyses reveal two peaks related to CO in high-frequency regions above 100 Hz associated with the anode polarization, with the peak integration being five times larger than in pure hydrogen. Humidification doesn't improve the voltage or mitigate CO poisoning. A one-dimensional flux model that includes the anode polarization is developed to analyze the polarizations for both cathode and anode under different concentrations of diluents, well describing the experimental results. When i < 0.8 A/cm2, the predicted values from the model closely match the measured values (within 5–10 mV). Calculations suggest that the anode polarization cannot be ignored, especially when the anode is fed with diluted gases.

Optimization of Manning's roughness coefficient using 1-dimensional hydrodynamic modelling in the perennial river system: A case of lower Narmada Basin, India.

This research bears significant implications for river management, flood forecasting, and ecosystem preservation in the Lower Narmada Basin. A more precise estimation of Manning's Roughness Coefficeint (n) will enhance the accuracy of hydraulic models and facilitate informed decision-making regarding flood risk management, water resource allocation, and environmental conservation efforts. Ultimately, this study aspires to contribute to the sustainable management of perennial river systems in India and beyond by offering a robust methodology for optimizing Manning's n tailored to the complex hydrological dynamics of the Lower Narmada Basin. Through a synthesis of empirical evidence and computational modelling, it seeks to empower stakeholders with actionable insights toward preserving and enhancing these invaluable natural resources. Using the new HEC-RAS v 6.0, a one-dimensional hydrodynamic model was developed to predict overbank discharge at different points along the basin. The study analyzes water levels, stream discharges, and river stage, optimizing Manning's n and required flood risk management. The model predicted a strong output agreement with R2, NSE, and RMSE for the 2020 eventas 0.83, 0.81, and 0.36, respectively, with an optimum Manning's n of 0.03. The lower Narmada Basin part near the coastal zone (validation point) appears inundated frequently. The paper aims to provide insights into optimizing Manning's coefficient, which can ultimately lead to better water flow predictions and more efficient water management in the region.

Hydraulic Transport of Large Solid Particles in Inclined Pipes under Pulsating Flow Conditions

Abstract The pressure loss due to the hydraulic transport of large solid particles should be predicted for the design of subsea mining systems. The mixture flow in a flexible jumper is expected to be unsteady during lifting operations in an actual mining system. The authors develop a one-dimensional mathematical model that predicts such pressure loss under pulsating mixture flows in a static inclined pipe assuming that the flow in the jumper is fully developed. An experiment is performed on the hydraulic transport of solid particles to obtain data for model validation. In this experiment, several kinds of solid particles are used: alumina beads, glass beads, and gravel. The experimental parameters are mixture velocity, solid concentration, pulsation period and amplitude of water velocity, and pipe inclination angle. The proposed model is validated through a comparison with experimental data. Furthermore, we calculate the pressure loss due to the hydraulic transport of polymetallic sulfide ores using the proposed model. The calculation results show that the time-averaged pressure loss drastically varies with the pipe inclination angle, reaching its maximum value between the pipe inclination angles of 30° and 60°, at which the flow is inclined upward. The results also show that the amplitude of pressure loss pulsation differs little between pipe inclination angles and that the pulsation component of pressure loss should be considered in designing lifting systems.

Quantum phase transitions in one-dimensional nanostructures: a comparison between DFT and DMRG methodologies.

In the realm of quantum chemistry, the accurate prediction of electronic structure and properties of nanostructures remains a formidable challenge. Density functional theory (DFT) and density matrix renormalization group (DMRG) have emerged as two powerful computational methods for addressing electronic correlation effects in diverse molecular systems. We compare ground-state energies ( ), density profiles ( ), and average entanglement entropies ( ) in metals, insulators and at the transition from metal to insulator, in homogeneous, superlattices, and harmonically confined chains described by the fermionic one-dimensional Hubbard model. While for the homogeneous systems, there is a clear hierarchy between the deviations, , and all the deviations decrease with the chain size; for superlattices and harmonic confinement, the relation among the deviations is less trivial and strongly dependent on the superlattice structure and the confinement strength considered. For the superlattices, in general, increasing the number of impurities in the unit cell represents lower precision in the DFT calculations. For the confined chains, DFT performs better for metallic phases, while the highest deviations appear for the Mott and band-insulator phases. This work provides a comprehensive comparative analysis of these methodologies, shedding light on their respective strengths, limitations, and applications. The DFT calculations were performed using the standard Kohn-Sham scheme within the BALDA approach. It integrated the numerical Bethe-Ansatz (BA) solution of the Hubbard model as the homogeneous density functional within a local-density approximation (LDA) for the exchange-correlation energy. The DMRG algorithms were implemented using the ITensor library, which is based on the matrix product states (MPS) ansatz. The calculations were performed until the energy reaches convergence of at least .

Lifshitz transitions and Weyl semimetals from a topological superconductor with supercurrent flow

A current flowing through a superconductor induces a spatial modulation in its superconducting order parameter, characterized by a wave vector Q related to the total momentum of a Cooper pair. Here we investigate this phenomenon in a p-wave topological superconductor, described by a one-dimensional Kitaev model. We demonstrate that, by treating Q as an extra synthetic dimension, the current-carrying nonequilibrium steady state can be mapped into the ground state of a half-filled two-dimensional Weyl semimetal, whose Fermi surface exhibits Lifshitz transitions when varying the model parameters. Specifically, the transition from type-I to type-II Weyl phases corresponds to the emergence of a gapless p-wave superconductor, where Cooper pairs coexist with unpaired electrons and holes. Such a transition is signaled by the appearance of a sharp cusp in the Q-dependence of the supercurrent, at a critical value Q* that is robust to variations of the chemical potential μ. We determine the maximal current that the system can sustain in the topological phase, and we discuss possible implementations. Published by the American Physical Society 2024

The Water Hammer Characteristics of Long-Distance Water Pipelines under Different Water Supply Modes

The pressure characteristics of long-distance water pipelines during hydraulic transient processes are crucial for ensuring the safe, stable, and long-term operation of water transfer projects. This paper establishes a one-dimensional mathematical model based on sections of the Yinjiangjihuai long-distance water diversion project in China. The water supply requirements of the pipelines are categorized into two replenishment modes as follows: gravity supply and pump-pressurized water supply. The opening and closing strategies of the water pipelines under different flow conditions are simulated and analyzed to explore the hydraulic transient processes under various water supply modes. The transient variations of key hydraulic parameters during valve closure are clarified. Simulation results indicate that the water pipeline design is reasonable, meeting the water supply demands at relatively low Manning values and that it has the capability for long-term supply. Due to the excessive head provided by the pumps, pump-pressurized water supply and gravity supply modes cannot operate simultaneously. Under gravity supply mode, the minimum pressure in the downstream pipeline is relatively higher overall, while the maximum pressure in the upstream pipeline is relatively lower overall. In the pump-pressurized water supply mode, the safety and stability of the water supply can be ensured by adjusting the closing time of individual pumps and the interval time between adjacent pumps. The research findings provide technical guidance and scientific basis for the construction of national water networks and water transfer projects.

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal–cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. The temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code’s covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

Dimensional effects in analysis of laser-induced-desorption diagnostics data

The accurate assessment of the local tritium concentration in the tokamak first wall by means of the laser-induced desorption (LID) diagnostics is sought as one the key solutions to monitoring the local radioactive tritium content in the first wall of the fusion reactor ITER. Numerical models of gas desorption from solids used for LID simulation are usually closed with the one-dimensional transport models. In this study, the temperature and particle dynamics in the target irradiated by a short laser pulse during LID are analyzed by means of the two-dimensional model to assess the validity of using one-dimensional approximation for recovering the diagnostics signal. The quantitative estimates for the parameters governing the heat and particle transfer are presented. The analytical expressions for the sample spatiotemporal temperature profiles driven by the target irradiation with a Gaussian laser beam with the trapezoid temporal shape are derived. The obtained relations are used to simulate tritium desorption from a tungsten sample driven by pulsed heating. It is shown that depending on the ratio between the laser spot radius and the heat diffusion length, the one-dimensional approach can noticeably overestimate the sample temperature in the limit of small laser spot radius (estimated for tungsten as ∼0.5–1.0 mm), resulting in more than 100% larger amounts of tritium desorbed from the target, compared to the two-dimensional approximation. In the limit of large laser spot radius (≥1.5 mm), both approaches yield comparable amounts of tritium desorbed from the sample.

Numerical Simulation and Experimental Comparison of System Analysis Module 1D Mixing Model for Cold Shock Transients in the Gallium Thermal-Hydraulic Mixing Facility

Liquid metals are being investigated as coolants in many advanced reactor designs because of their high thermal conductivity and effectiveness at high temperatures. However, they often pose challenges to reactor operation and safety because of the complex thermal mixing and stratification in the plenum of pool-type reactor designs. The advanced system analysis code System Analysis Module (SAM) currently under development at Argonne National Laboratory aims to develop and implement thermal mixing models to accurately capture these complex thermal fluid behaviors. In this study, the SAM thermal mixing model was compared against experimental data from the Gallium Thermal-Hydraulic Experiment facility, a scaled liquid metal test facility that uses gallium as a surrogate fluid to investigate the stratification and thermal mixing of low-Prandtl-number fluids in the upper plenum of a liquid metal–cooled reactor. Two cold shock transient cases were used: one with stable stratified flow (Ri = 32) and one with stronger thermal mixing (Ri = 0.5). The resultant temperatures were then compared with the experimental temperatures over the entire plenum to assess the ability of the mixing models to capture the thermal behavior and to better correspond mixing parameters to various flow scenarios. Generally, the zero-dimensional mixing model was more capable of capturing the bulk temperature of the component modeled assuming that an accurate mass flow rate was provided, but it was inherently unable to capture thermal gradients in space. The one-dimensional mixing model was capable of capturing that the thermal gradients provided accurate selection of the mixing coefficients. The temperature at the outlet junction was compared over time for each of the mixing models with the recorded experimental temperature. The implemented mixing models demonstrated the ability to effectively capture the overall thermal behavior for stronger mixing scenarios but struggled with more stably stratified flows. It was found that a system analysis code’s covering of the entire range of different operating conditions still remains a challenging task, and it is suggested that further model and closure improvements are necessary to accurately capture complex thermal mixing and stratification phenomena.

Promoting precision surface irrigation through hydrodynamic modelling and microtopographic survey

Precision irrigation aims to deliver water and nutrients to crops at exactly the right time, in the right place and in the right amount. While surface irrigation is often perceived as less precise, accurate water distribution, wise use of resources and high efficiency can still be achieved with careful land preparation, astute irrigation management and rigorous performance monitoring. In this study, we advocate the innovative concept of Precision Surface Irrigation, centered around three key design and operational principles that are: well-organized field geometry (and microtopography), precise control of hydraulic-hydrological variables and, finally, regular performance evaluation. These pillars are then integrated into a simulation environment capable of capturing the intricacies of surface irrigation dynamics. Conducted in northern Italy's Padana plain, the study contrasts one-dimensional (WinSRFR) and two-dimensional (IrriSurf2D) irrigation dynamic modeling. Data collection includes boundary geometries, inflow rates, intervention durations, and microtopography, facilitating spatial performance assessment from both the models. The results show that the versatility of the two-dimensional modelling approach was able to reproduce well the observed water depths and the phases of water advance and depletion both in time and space within the studied border irrigation strips, even in complex situations where the strips were hydraulically connected. The RMSE between observed and simulated maximum water depth and waterfront advance time was less than 2.1 cm and 1.9 min, respectively. The two-dimensional approach was also able to detect the cross variability of irrigation dynamics, and to provide a spatial assessment of irrigation performance at high resolution. In conclusion, while the one-dimensional hydrodynamic approach to describing the hydraulic behavior of surface irrigation and field-scale irrigation performance remains valid, the two-dimensional approach provides, in our case study and reasonably elsewhere, a valid simulation environment for spatially characterizing irrigation dynamics in the context of Precision Surface Irrigation.

Numerical modeling of heat transfer behavior for two-phase flow in a nozzle considering phase change

The heat transfer and phase change of alumina particles in the gas-particle flow of the nozzle plays an important role in solid rocket motors (SRM) due to the coupling between the heat transfer and two-phase flow. However, it lacks precise modeling of the heat transfer behaviors of condensed particles in the nozzle, especially the phase change effect. In this article, we determine that the Drake model has the highest accuracy in calculating the convective heat flux between two phases, and propose a correlation to obtain radiative heat flux between the particle and walls. Then, a one-dimensional two-phase non-equilibrium model is established to consider the effects of heat transfer and solidification of particles on the two-phase flow in the nozzle. The results show that considering the phase change of particle improves the outlet thrust of the nozzle, but such increment decreases with the gas inlet temperature. When the supercooling phenomenon is considered, the nozzle thrust is reduced by 1.14% compared with that considering no supercooling. As the particle size increases, the outlet temperature of the particle phase rises and can even surpass the solidification temperature of particles and the velocity of the particle phase decreases significantly.

NITIRSOIL: A model that balances complexity with prediction uncertainty for improving nitrogen fertilization in agriculture

Mismanagement of the nitrogen (N) fertilization in agriculture leads to low N use efficiency (NUE) and therefore pollution of waters and atmosphere due to NO3− leaching, and N2O and NH3 emissions. The use of N simulation models of the soil-plant system can help improve the N fertilizer management increasing NUE and decreasing N pollution issues. However, many N simulation models lack balance between complexity and uncertainty with the result that they are not applied in actual practice. The NITIRSOIL is a one-dimensional transient-state model with a monthly time step that aims at addressing this lack in the estimation of, mainly, dry matter yield (DMY), crop N uptake (Nupt), soil mineral N (Nmin), and NO3− leaching in agricultural fields. According to its global sensitivity analysis for horticulture, the NITIRSOIL simulations of the aforementioned outputs mostly depend on the critical N dilution curve, harvest index, dry matter fraction, potential fresh yield and nitrification coefficients. According to its validation for 35 nitrogen fertilization trials with 11 vegetables under semi-arid Mediterranean climate in Eastern Spain, the NITIRSOIL presents indices of agreement between 0.87 and 0.97 for the prediction of total dry matter, DMY, Nupt, NO3− leaching and soil Nmin at crop season end. Therefore, the NITIRSOIL model can be used in actual practice to improve the sustainability of the N management in, particularly horticulture, due to the balance it features between complexity and prediction uncertainty. For this aim, the NITRISOIL can be used either on its own, or in combination with “Nmin” on-site N fertilization recommendation methods, or even could be implemented as the calculation core of decision support systems.

Development of performance analysis model with numerical and dynamic energy modeling for an integrated PVT-HP system

This study delivers a comprehensive numerical analysis of an integrated photovoltaic/thermal-heat pump (PVT-HP) system, underscored by an innovative three-dimensional thermal energy storage (TES) model. Addressing the limitations of conventional one-dimensional TES models, which struggled with accurately simulating horizontal flows and the fluid state at various facility inlets, this research marks a significant advancement. Our development of a 3D TES model optimizes finite elements to reduce computation time and enhance accuracy, vital for precise energy analysis in buildings and air conditioning systems. The integration of this model with a network model allows for detailed analysis of flow rate changes and their impacts on heat transfer, crucial for the integrated PVT-HP system. Key findings include a 30 % increase in the temperature difference between the top and bottom layers of the TES when the flow rate is reduced from 50 LPM to 20 LPM, and a 1 % decrease in the heat pump's coefficient of performance (COP) with a 10 LPM reduction in flow rate. The study emphasizes that managing the flow rate is key to optimizing temperature gradients and system efficiency. Strategic adjustments in flow rate significantly affect thermal storage and transfer capabilities, proving essential in system performance. This research offers vital insights into optimizing PVT-HP systems, focusing on the importance of flow rate control in improving temperature management and overall system performance.

Analytical and numerical calculation of the effect of edge states of the Kane-Mele model on the RKKY interaction

In this paper, we investigate the Kane-Mele model and endeavor to demonstrate, through analytical calculations, how the presence of topological edge states influences the RKKY interaction. We illustrate that the effect diminishes as one moves away from the edges. To facilitate our analytical approach, we initially utilize a one-dimensional wire exhibiting linear dispersion for each spin as an approximation to the Kane-Mele model. We examine its impact on the RKKY interaction. Subsequently, we establish a correspondence between the edge states of the Kane-Mele model and a one-dimensional quantum wire model, wherein the coupling strength diminishes with increasing distance from the edges. Finally, we compare the analytical results with numerical findings obtained using the Landauer-Buttiker formulation.

Propagation Characteristics of Initial Compression Wave Induced by 400 km/h High-Speed Trains Passing through Very Long Tunnels

When high-speed trains enter tunnels, an initial compression wave is generated. As the compression wave propagates at the local speed of sound to the tunnel exit, it radiates into the surrounding environment, forming micro-pressure waves (MPWs). MPWs create sonic booms, resulting in significant environmental issues. The magnitude of the micro-pressure waves is directly proportional to the pressure gradient of the compression wave at the tunnel exit. The nonlinear effects of the initial compression wave during propagation lead to a significant increase in pressure gradient. Therefore, the propagation characteristics of the initial compression wave during the tunnel are the crucial factor affecting the amplitude of MPWs. Based on the one-dimensional compressible unsteady non-isentropic flow model and the improved generalized Riemann variable characteristic method, this paper researched the propagation and evolution characteristics of an initial compression wave generated when 400 km/h high-speed trains enter tunnels with three portal shapes: (no tunnel entrance hood (no hood), an oblique, enlarged tunnel entrance hood (type A), an enlarged equal-section non-uniform opening hole tunnel entrance hood (type B)). The results show that when the initial compression wave propagates inside very long tunnels, the pressure gradient of the compression wave exhibits a trend of initially increasing and then decreasing with the increase in propagation distance. When the pressure gradient of the compression wave reaches its maximum value, the corresponding propagation distance is the steepening critical distance. For no tunnel entrance hoods, type A tunnel entrance hoods, and type B tunnel entrance hoods, the steepening critical distances are 5 km, 6 km, and 16 km, respectively. The steepening critical distance shortens with increasing train speed. Steady friction and unsteady friction effects mainly affect the pressure amplitude and pressure gradient during compression wave propagation, respectively. At lower ambient temperatures, the nonlinear effects in compression wave propagation are significantly enhanced. The mitigation effects of type A tunnel entrance hoods and type B tunnel entrance hoods on pressure gradient reduction are mainly concentrated within 4 km and 12 km, respectively. It is necessary to determine the optimal matching relationship between the tunnel entrance hood and tunnel length based on the characteristics of compression wave propagation to ensure their mitigating performance is maximized.

Propagation Characteristics of Initial Compression Wave Induced by 400 km/h High-Speed Trains Passing through Very Long Tunnels

When high-speed trains enter tunnels, an initial compression wave is generated. As the compression wave propagates at the local speed of sound to the tunnel exit, it radiates into the surrounding environment, forming micro-pressure waves (MPWs). MPWs create sonic booms, resulting in significant environmental issues. The magnitude of the micro-pressure waves is directly proportional to the pressure gradient of the compression wave at the tunnel exit. The nonlinear effects of the initial compression wave during propagation lead to a significant increase in pressure gradient. Therefore, the propagation characteristics of the initial compression wave during the tunnel are the crucial factor affecting the amplitude of MPWs. Based on the one-dimensional compressible unsteady non-isentropic flow model and the improved generalized Riemann variable characteristic method, this paper researched the propagation and evolution characteristics of an initial compression wave generated when 400 km/h high-speed trains enter tunnels with three portal shapes: (no tunnel entrance hood (no hood), an oblique, enlarged tunnel entrance hood (type A), an enlarged equal-section non-uniform opening hole tunnel entrance hood (type B)). The results show that when the initial compression wave propagates inside very long tunnels, the pressure gradient of the compression wave exhibits a trend of initially increasing and then decreasing with the increase in propagation distance. When the pressure gradient of the compression wave reaches its maximum value, the corresponding propagation distance is the steepening critical distance. For no tunnel entrance hoods, type A tunnel entrance hoods, and type B tunnel entrance hoods, the steepening critical distances are 5 km, 6 km, and 16 km, respectively. The steepening critical distance shortens with increasing train speed. Steady friction and unsteady friction effects mainly affect the pressure amplitude and pressure gradient during compression wave propagation, respectively. At lower ambient temperatures, the nonlinear effects in compression wave propagation are significantly enhanced. The mitigation effects of type A tunnel entrance hoods and type B tunnel entrance hoods on pressure gradient reduction are mainly concentrated within 4 km and 12 km, respectively. It is necessary to determine the optimal matching relationship between the tunnel entrance hood and tunnel length based on the characteristics of compression wave propagation to ensure their mitigating performance is maximized.

Prediction method of human defecation based on informer audio data augmentation and improved residual network

Defecation care for disabled patients is a major challenge in health management. Traditional post-defecation treatment will bring physical injury and negative emotions to patients, while existing pre-defecation forecasting care methods are physically intrusive. On the basis of exploring the mechanism of defecation intention generation, and based on the characteristic analysis and clinical application of bowel sounds, it is found that the generation of desire to defecate and bowel sounds are correlated to a certain extent. Therefore, a deep learning-based bowel sound recognition method is proposed for human defecation prediction. The wavelet domain based Wiener filter is used to filter the bowel sound data to reduce other noise. Statistical analysis, fast Fourier transform and wavelet packet transform are used to extract the integrated features of bowel sound in time, frequency and time-frequency domain. In particular, an audio signal expansion data algorithm based on the Informer model is proposed to solve the problem of poor generalization of the training model caused by the difficulty of collecting bowel sound in reality. An improved one-dimensional residual network model (1D-IResNet) for defecation classification prediction is designed based on multi-domain features. The experimental results show that the proposed bowel sound augmentation strategy can effectively improve the data sample size and increase the sample diversity. Under the augmented dataset, the training speed of the 1D-IResNet model is accelerated, and the classification accuracy reaches 90.54 %, the F1 score reaches 83.88 %, which achieves a relatively good classification stability while maintaining a high classification index.

Level statistics of the one-dimensional dimerized Hubbard model

The statistical properties of level spacings provide valuable insights into the dynamical properties of a many-body quantum systems. We investigate the level statistics of the Fermi–Hubbard model with dimerized hopping amplitude and find that after taking into account translation, reflection, spin and η pairing symmetries to isolate irreducible blocks of the Hamiltonian, the level spacings in the limit of large system sizes follow the distribution expected for hermitian random matrices from the Gaussian orthogonal ensemble. We show this by analyzing the distribution of the ratios of consecutive level spacings in this system, its cumulative distribution and quantify the deviations of the distributions using their mean, standard deviation and skewness.

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall.

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process-structure-property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process-structure-property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

Thermal effect of VIPV modules in refrigerated trucks

The integration of Photovoltaic (PV) modules within the outer structure of commercial transporters offers a great potential as an additional source of energy that can be utilized, for example, directly by the drive train of the vehicle, or by accessory equipment. However, to understand the benefits of such a system, the effect and relevance of some thermodynamic variables introduced by the Vehicle Integrated Photovoltaic (VIPV) system must be assessed. Particularly, the share of the solar irradiance that cannot be converted into electricity by the solar cell and is instead transformed into heat must be considered for certain applications such as the transportation of goods that require a controlled temperature. A one-dimensional thermal simulation model based on a Resistance-Capacitance methodology was created and validated experimentally. The model was used to predict the thermal behavior of the box-body of a truck for a representative year in three cities in Europe (Stockholm, Freiburg, and Seville), with a known Bill of Materials (BOM), and a set of given assumptions and constraints. It was found that, under the simulated conditions laid in this study, the additional heat generated by the PV modules that manages to go through the insulation material and reach the refrigerated cargo area, may raise the temperature of the contained air by an average of 0.36 °C, 0.5 °C, and 0.67 °C, respectively for the observed cities, and as much as 3.12 °C, 2.98 °C and 2.61 °C. When forced convection caused by the movement of the truck was applied into the model (with a constant wind speed of 50 km/h), the temperature of the solar cell dropped significantly, which, for the case of Freiburg, meant an increase in the contained air temperature of a maximum of 0.6 °C. A refrigeration system was subsequently considered for a target air temperature of 2 °C and −18 °C, and it was found that for the simulated scenarios, the harvested solar energy could easily offset the additional energetic demand caused by the PV system, and, in most cases, completely balance out the total annual demand of the chiller.