Temperature-dependent Model Research Articles

Seasonal forecasting of pest population dynamics based on downscaled SEAS5 forecasts

Among the varied environmental factors that influence insect life-history, temperature has a relatively profound effect that can be mathematically estimated with non-linear equations. Thus, many models that aim to predict insect-pest population dynamics use meteorological data as input to descriptive functions that predict the development rate, survival and reproduction of pest populations. In a previous study, we developed a temperature-dependent population dynamics model for the global insect-pest Bemisia tabaci, and verified its accuracy under field conditions. In the current work, which focused on Northern Israel, seasonal meteorological forecasts from the ECMWF SEAS5 coupled model were spatially and temporally stochastically downscaled by a weather generator tool using records from ERA5-Land reanalysis and meteorological stations. The local, hourly temperature time series served as input data to a population dynamics model, creating an ensemble of seasonal population forecasts from which probabilistic predictions could be made already at the beginning of the season (which lasts from March to November). Post-hoc evaluation of the seasonal forecast was done using the observed station temperatures as model input. Comparisons to predictions made using climatologic temperatures found the weather generator-based ones much more accurate in predicting the timing of each insect generation, although there was no difference between the two approaches in predicting the population size. Moreover, the weather generator-based predictions highly matched field observations made by pest inspectors during the growing season of 2021. Taken together, our findings indicate that the developed forecasting tool is capable of providing decision makers with the supporting data required for smart seasonal planning and economical- and environmental-driven optimal management of agricultural systems.

Behavior and Capacity of Moment-Frame Members and Connections during Fire

This paper focuses on investigating the structural behavior of members and connections that are part of moment frames under the combined effect of bending moment and thermally induced axial force during a compartment-fire event. The finite-element analysis method was employed to conduct this study using models benchmarked against experimental data from several past studies while utilizing temperature-dependent material models. A numerical parametric study on typical floor beams with slender elements for compression were conducted under combined bending and axial loading to develop interaction-capacity curves at temperatures representing fire events. The results were compared against the member-strength equations provided in the AISC Specification. The analysis results demonstrated that the AISC beam-column strength equations including the combined effects of axial-load and bending moment provided reasonable estimates for member-slenderness ratios greater than 60, but overestimated the strength of beams with slender elements for low member-slenderness ratios. Combined-load-strength studies were also conducted on a typical connection used in moment frames. The moment-connection behavior was governed by failure modes exhibited at the ends of floor beams. Therefore, the interaction equations available for beam columns resulted in conservative estimates and are recommended for calculating moment-connection capacity during compartment-fire scenarios.

Non-fitting theoretical models for the fracture properties of concretes subjected to high temperature

The fracture properties of concretes, which are often characterized by the tensile fracture strength, compressive fracture strength, fracture energy and characteristic length are closely related to temperature. However, there are still few systematic theoretical models of temperature-dependent fracture properties of concretes. In this work, a series of novel temperature-dependent theoretical models are developed to determine the fracture properties of concretes based on the force-heat equivalence energy density principle and classical concrete fracture theories. The models establish the quantitative relationship between the high-temperature tensile fracture strength, compressive fracture strength and characteristic length, and the basic material parameters including the Young's modulus and melting point. It is worth noting that this work quantitatively characterizes the fracture properties of concretes subjected to high temperatures using the simple material parameters, without the need to carry out any data fitting. The fracture properties of concretes with different aggregate types, different fiber-reinforced concretes, and ordinary Portland cement-based concretes are predicted and systematically analyzed using the proposed models. The model-predicted tensile fracture strength, compressive fracture strength and characteristic length of materials up to 800 °C agree well with the experimental measurements without using any fitting parameters. The coincidence rate at many temperature points could reach up to and above 90%, even approaching about 100%. The fracture properties of concretes and their main mechanisms at various temperatures thus can be depicted by using the developed models. Additionally, this work offers a new and simple testing method to determine the characteristic length of concretes and its change with temperature.

Supercritical CO2 permeation in polymeric films: Design, characterization, and modeling

This study is concerned with the development of an optimum method for identification of supercritical CO2 permeability in thermoplastic films with moderate to excellent barrier properties namely, High-Density Polyethylene (HDPE), Raised-Temperature Polyethylene (PE-RT), Polyvinylidene Fluoride (PVDF) and aliphatic Polyketone (PK) at elevated temperatures (40 °C−82 °C). A high-temperature/high-pressure permeation cell was designed based on the “closed-volume/variable pressure” standard test method. The identified gas transport properties using the time lag method yielded significant error particularly for PVDF and PK, which was ascribed to the sole reliance on the accumulated pressure-rate in steady-state. This error was minimized using the Non-Linear Regression (NLR) by utilizing the full range of measured data including the transient state. The coefficient of determination between the measured and modeled data using NLR was quantified above 0.99 for all the polymers at the entire examined temperature range. The 1.4 % higher degree of crystallinity and 28.5 % smaller spherulite size caused 13.3 % higher diffusivity and 8.6 % lower solubility in PE-RT when compared with HDPE at 82°C. As a result of this trade-off, PE-RT exhibited only 3.5 % higher permeability than HDPE. The developed generalized temperature-dependent model provided the essential data for design optimization of gas barrier performance in multilayer high-temperature pressure-vessels.

A temperature-dependent elastoplastic damage model for frozen sandstone

Subzero temperature has a significant effect on mechanical behaviors of rocks. When a sandstone is in subzero temperature environments, the sandstone exhibits temperature-dependent mechanical characteristics due to the freezing of pore water and the shrinkage of mineral particles. To disclose the influence of subzero temperature on the mechanical behaviors of the frozen sandstone, triaxial compressive tests were carried out at four confining pressures (0 MPa, 1 MPa, 3 MPa, 5 MPa) and four subzero temperatures (0 °C, −5 °C, −10 °C, −15 °C). The laboratory tests show that the frozen sandstone undergoes four typical deformation stages from initial loading to failure: compaction, elasticity, yield and postpeak failure stage. With the temperature decreasing, the compaction stage gradually shortens, and the nonlinear behavior of yield stage weakens. The peak strength and initial yield stress of the frozen sandstone increase, and the initial and ultimate yield surfaces expand gradually with decreasing temperature. Based on the deformation features of the frozen sandstone, an elastoplastic damage model is established by considering the effect of subzero temperature on the yield process and deformation. The elastoplastic damage model was calibrated by the experimental data, and the comparisons demonstrate that the proposed constitutive model well agrees with the stress–strain curves at the four subzero temperatures. An exponential evolution law of the macroscopic damage is found in the elastoplastic model, which is totally consistent with the microscopic damage variation monitored by the acoustic emission (AE) technology. Therefore, the temperature-dependent elastoplastic model can well predict the whole deformation behaviors of the sandstone under different subzero temperatures and gives a quantitative description on the damage evolution, and may serve as theoretical references for the construction and safety operation of frozen rock masses in cold regions.

A Temperature-Dependent Viscoplasticity Model for the Hot Work Steel X38CrMoV5-3, Including Thermal and Cyclic Softening under Thermomechanical Fatigue Loading.

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.

Analysis of a temperature-dependent model for water-borne disease transmission dynamics

Analysis of a temperature-dependent model for water-borne disease transmission dynamics

Temperature-dependent model for ferroelectrics embedded into two-dimensional polygonal finite element framework

A two-dimensional constitutive model, which is based on micromechanical rotation of domains, is presented in this work to demonstrate the non-linear behavior of ferroelectric materials under different loading conditions. A temperature-dependent combined material model that incorporates both phases i.e., tetragonal and rhombohedral phases is embedded into two-dimensional polygonal finite element framework. The developed material model which has easily overcome shortcomings related to tetragonal model and rhombohedral model alone. This model is developed on the morphotropic phase boundary which has produced desired behavior based on macroscopic material parameters. Temperature effects on behavior of combined material model are obtained in the work. Furthermore, polarization rotation test and temperature effects on polarization rotation are also studied in present work. There are numerous studies conducted on ferroelectric materials. All of them incorporate behavior of ferroelectric material confined to specific conditions. Either tetragonal model or rhombohedral model has been used extensively to get the desired behavior based on macroscopic material parameters. This model has some limitations in either satisfying one or another condition related to experiments conducted to study the behavior of ferroelectric materials. The tetragonal material model is capable of producing results with microscopic material properties but in case of macroscopic material parameters the tetragonal model is insufficient to produce the desired behavior for PZT ceramics. The rhombohedral material model is sufficient to produce results based on macroscopic material parameters. Therefore, model is extended by rhombohedral phase, allowing a mixture of both phases with varying quantities inside the grain. Though, rhombohedral model is also not used to that extent. We have developed material model that gives desired behavior and overcomes the hurdles in the existing model.

Temperature-Dependent Ferromagnetic Loss Approximation of an Induction Machine Stator Core Material Based on Laboratory Test Measurements

The accurate measurement and modeling of ferromagnetic material losses are vital issues during the design and analysis of electrical machines. Higher loss values can describe the manufactured rotor and stator machine plates better than the catalog data obtained by standardized measurements using the Epstein frame. In this paper, different temperature-dependent models based on the loss-separation principle are introduced and compared with the measurements. The model parameters are computed from customized laboratory and standardized measurements. The customized measurements based on the stator part of an induction machine in the range of the automotive industry standard, i.e., in [−40 °C, ⋯, 180 °C]. The proposed model and measurement process can be used in the post-processing stage of numerical field analysis to obtain electromagnetic losses according to the agreement between measured and simulated results. During a numerically expensive optimization process, this model can be used to consider the temperature dependence of the losses more accurately. The study shows that more than 50% of loss increase can be measured, compared with the catalog data, if we use the manufactured, stator-based, customized measurements based on the estimation of the iron loss parameters.

Plasmonic photothermal therapy in the near-IR region using gold nanostars.

Photothermal therapy using nanoparticles is a prominent technique for cancer treatment. The principle is to maximize the heat conversion efficiency using plasmonic nanoparticle-light interaction. Due to their unique optical characteristics derived from their anisotropic structure, gold nanostars (GNSs) have gotten significant attention in photothermal therapy. To design a proper cancer treatment, it is vital to study the thermal effect induced close to the gold nanoparticles, in the vicinity, and the cancerous tissue. A temperature-dependent 2D model based on finite element method models is commonly used to simulate near-IR tumor ablation. The bioheat equation describes the photothermal effect within the GNSs and the environment. Surface cooling and heating strategies, such as the periodical heating method and a reduced laser irradiation area, were investigated to address surface overheating problems. We also determined that the optimal laser radius depends on tumor aspect ratio and laser intensity. Our results provide guidelines to evaluate a safe and feasible temperature range, treatment time, optimal laser intensity, and laser radius to annihilate a tumor volume.

Temperature-dependent CO2 line mixing models using dual frequency comb absorption and phase spectroscopy up to 25 bar and 1000 K

We perform dual frequency comb laser absorption spectroscopy of CO2 at high pressure and temperature, and use the spectra to test and improve CO2 line mixing models and their temperature dependence. The dual-comb spectrometer spans 6800–7000 cm−1 with 0.0066 cm−1 point spacing, and is coupled to a specialized, high-pressure, high-temperature gas cell providing conditions up to 977 K and 25 bar. We compare our measurements to spectra calculated using an advanced line mixing model for pure CO2 based on the energy-corrected sudden (ECS) approximation. We determine a new set of temperature-dependent ECS model parameters, and show that the new parameters significantly improve the accuracy of the ECS line mixing model over a temperature range spanning 298–977 K. We also compare the measured spectra to a simpler line mixing model developed using the modified exponential gap (MEG) scaling law, and report the temperature and pressure dependence of the MEG model parameters required to scale the model across wide ranges of conditions. Finally, we report high-pressure, ambient-temperature measurements of CO2 spectra in both amplitude (absorption) and phase using the dual-comb spectrometer. We use these measured absorption and phase spectra to assess the performance of the ECS and MEG line mixing models at high densities near room temperature. To the best of our knowledge, these results represent the first study of line mixing using phase spectroscopy. Overall, the results of this study significantly expand line mixing models for CO2 at high pressure and temperature and improve the accuracy and availability of absorption models for harsh conditions encountered in laser-based sensing and planetary science.

Developmental Differentiations of Major Maize Stemborers Due to Global Warming in Temperate and Tropical Climates

While many insects are in decline due to global warming, the effect of rising temperatures on crop insect pests is uncertain. A capacity to understand future changes in crop pest populations remains critical to ensure food security. Using temperature-dependent mathematical models of the development of four maize stemborers in temperate and tropical regions, we evaluated the potential impacts of different climate change scenarios on development time. While recognizing the limitations of the temperature-dependent development rate approach, we found that global warming could either be beneficial or detrimental to pest development, depending on the optimal temperature for the development of the species and scenarios of climate change. Expected responses range from null development to 1.5 times faster development than expected today. These results suggest that in the medium term, the studied species could benefit from global warming with an accelerated development, while in the long term, their development could either be delayed or accelerated, which may impact their dynamics with implications on maize cultivation.

A coarse-grained simulation model for colloidal self-assembly via explicit mobile binders.

Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet-droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed 'colloidomers', which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. We explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.

Battery lifetime of electric vehicles by novel rainflow-counting algorithm with temperature and C-rate dynamics: Effects of fast charging, user habits, vehicle-to-grid and climate zones

The adoption of electric vehicles is expected to soon widespread to cope with energy transition needs; however, concerns on battery lifetime arise, especially related to charging behaviors, vehicle usage habits, vehicle-to-grid and weather conditions. In fact, lifetime battery modeling is a challenging dynamic to characterize, as it involves complex chemical processes related to charging, discharging and temperature dynamics over long time spans that are often difficult to dominate, given the large uncertainties. Having a fatigue-like behavior, the battery aging has sometimes been modeled using rainflow-counting algorithms, yet traditional modeling is not holistic and approximations are used, especially when considering temperature or current dynamics. Based on experimental data, this paper aims at developing a holistic battery degradation model based on rainflow-counting algorithm to properly account for all major determinants of capacity loss, namely cycling usage, calendar lifetime, dynamic temperature and battery current. The approach is coupled with a physical-electro-thermal modeling of the vehicle system, developed in Modelica language, to accurately simulate the intertwined thermal and electrical behavior of the system subject to different usage charging behaviors, including slow and fast charging, as well as vehicle-to-grid application. The proposed case study shows the expected lifetime of electric vehicles to be comparable with of traditional cars (10–20y) and that the proposed temperature-dependent battery modeling enables reducing estimation errors up to 27%. A sensitivity on different climate zones has been considered and results suggest that cool climates can increase life expectancy by 30% with respect to hot climates in typical Italian contexts.

Dosimetry Effects Due to the Presence of Fe Nanoparticles for Potential Combination of Hyperthermic Cancer Treatment with MRI-Based Image-Guided Radiotherapy

Nanoparticles have proven to be biocompatible and suitable for many biomedical applications. Currently, hyperthermia cancer treatments based on Fe nanoparticle infusion excited by alternating magnetic fields are commonly used. In addition to this, MRI-based image-guided radiotherapy represents, nowadays, one of the most promising accurate radiotherapy modalities. Hence, assessing the feasibility of combining both techniques requires preliminary characterization of the corresponding dosimetry effects. The present work reports on a theoretical and numerical simulation feasibility study aimed at pointing out preliminary dosimetry issues. Spatial dose distributions incorporating magnetic nanoparticles in MRI-based image-guided radiotherapy have been obtained by Monte Carlo simulation approaches accounting for all relevant radiation interaction properties as well as charged particles coupling with strong external magnetic fields, which are representative of typical MRI-LINAC devices. Two main effects have been evidenced: local dose enhancement (up to 60% at local level) within the infused volume, and non-negligible changes in the dose distribution at the interfaces between different tissues, developing to over 70% for low-density anatomical cavities. Moreover, cellular uptakes up to 10% have been modeled by means of considering different Fe nanoparticle concentrations. A theoretical temperature-dependent model for the thermal enhancement ratio (TER) has been used to account for radiosensitization due to hyperthermia. The outcomes demonstrated the reliability of the Monte Carlo approach in accounting for strong magnetic fields and mass distributions from patient-specific anatomy CT scans to assess dose distributions in MRI-based image-guided radiotherapy combined with magnetic nanoparticles, while the hyperthermic radiosensitization provides further and synergic contributions.

Linking spatial distribution of Rhipicephalus appendiculatus to climatic variables important for the successful biocontrol by Metarhizium anisopliae in Eastern Africa

Cattle production is constantly threatened by diseases like East Coast fever, also known as theileriosis, caused by the protozoan parasite Theileria parva which is transmitted by ticks such as the brown ear tick, Rhipicephalus appendiculatus. To reduce the extensive use of chemical acaricides, fungal-based microbial control agents such as Metarhizium anisopliae have been tested and show promising results against R. appendiculatus both in field and in semi-field experiments in Africa. However, no known endeavors to link the spatial distribution of R. appendiculatus to climatic variables important for the successful application of M. anisopliae in selected East African countries exists. This work therefore aims to improve the successful application of M. anisopliae against R. appendiculatus by designing a temperature-dependent model for the efficacy of M. anisopliae against three developmental stages (larvae, nymphs, adults) of R. appendiculatus. Afterward a spatial prediction of potential areas where this entomopathogenic fungus might cause a significant epizootic in R. appendiculatus population in three selected countries (Kenya, Tanzania, Uganda) in Eastern Africa were generated. This can help to determine whether the temperature and rainfall at a local or regional scale might give good conditions for application of M. anisopliae and successful microbial control of R. appendiculatus.

Temperature-Dependent modelling of tension, in-Plane shear, and bending behaviour in non-isothermal thermo-Stamping process simulation of unidirectional UHMWPE fibre reinforced thermoplastic TPU composites

This study proposes a macroscopic finite element modelling and simulation approach considering the temperature dependency of both in-plane membrane and out-of-plane bending behaviours. This approach enables the investigation of the effect of the deformation mechanisms on the quality of the formed thermoplastic composite parts during the thermo-forming process. The temperature-dependent constitutive model of the in-plane tensional behaviour is considered linear, whereas the in-plane shear stiffness is modelled based on the nonlinear hypoelastic constitutive equation. The out-of-plane bending behaviour is considered by decoupling the membrane and bending method. A numerical simulation strategy is developed by implementing the ABAQUS software via a VUMAT subroutine. Moreover, a modified method is introduced for the qualitative and quantitative assessment of the wrinkling intensity generated in the forming process. The validated strategy is used to investigate the influences of the various temperature conditions of the forming process and the underlying mechanisms to optimise the thermo-stamping process.

Temperature Extrapolation of Molecular Dynamics Simulations of Complex Chemistry to Microsecond Timescales Using Kinetic Models: Applications to Hydrocarbon Pyrolysis.

We develop a method to construct temperature-dependent kinetic models of hydrocarbon pyrolysis, based on information from molecular dynamics (MD) simulations of pyrolyzing systems in the high-temperature regime. MD simulations are currently a key tool to understand the mechanism of complex chemical processes such as pyrolysis and to observe their outcomes in different conditions, but these simulations are computationally expensive and typically limited to nanoseconds of simulation time. This limitation is inconsequential at high temperatures, where equilibrium is reached quickly, but at low temperatures, the system may not equilibrate within a tractable simulation timescale. In this work, we develop a method to construct kinetic models of hydrocarbon pyrolysis using the information from the high-temperature high-reactivity regime. We then extrapolate this model to low temperatures, which enables microsecond-long simulations to be performed. We show that this approach accurately predicts the time evolution of small molecules, as well as the size and composition of long carbon chains across a wide range of temperatures and compositions. Further, we show that the range of suitable temperatures for extrapolation can easily be improved by adding more simulations to the training data. Compared to experimental results, our kinetic model leads to similar compositional trends while allowing for more detailed kinetic and mechanistic insights.

On the Role of Damage Evolution in Finite Element Modeling of the Cutting Process and Sensing Residual Stresses.

This study focuses on the role of the damage evolution when estimating the failure behavior of AISI 1045 steel for sensing and measuring metal cutting parameters. A total of five Lagrangian explicit models are established to investigate the effect of applying damage evolution techniques. The Johnson-Cook failure model is introduced once to fully represent damage behavior, i.e., no damage evolution is considered, and as a damage initiation criterion in the remaining approaches. A fracture energy-based model is included to model damage propagation with different evolution rates. Temperature-dependent and temperature-independent fracture energy models are also investigated. Dry orthogonal cutting and residual stresses measurements of AISI 1045 are conducted for validation. The significance of the damage evolution is investigated using honed-tool and sharp-tool models. Including the damage evolution led to a prediction of higher workpiece temperatures, plastic strains, cutting forces, and residual stresses, with no clear differences between linear and exponential evolution rates. The role of damage evolution is more evident when temperature-dependent evolution models are used.

Analysis of electronic properties of dense plasma-embedded highly charged ions using temperature-dependent ion sphere model

Analysis of electronic properties of dense plasma-embedded highly charged ions using temperature-dependent ion sphere model