Search Results (12)

Though the pursuit of sustainable desalination processes with high water recovery has intensified the research interest in membrane distillation (MD), the influence of module connection configuration on performance stability remains poorly explored. The current study provided a comprehensive multiparameter assessment of hollow fibre membrane modules connected in parallel and series in direct contact membrane distillation (DCMD) for the first time. The configurations were evaluated under varying process parameters such as temperature (50–70 °C), flow rates (22.1–32.3 mL·s⁻¹), magnesium concentration as scalant (1.0–4.0 g·L⁻¹), and flow direction (co-current and counter-current), assessing their influence on temperature gradients (∆T), flux and pH stability, salt rejection, and crystallisation. Interestingly, the parallel module configuration maintained high operational stability with uniform flux and temperature differences (∆T) even at high recovery factors (>75%). On one hand, the serial configuration experienced fluctuating ∆T caused by thermal and concentration polarisation, causing an early crystallisation (abrupt drop in feed conductivity). Intensified polarisation effects with accelerated crystallisation increased the membrane risk of wetting, particularly at high recovery factors. Despite these changes, the salt rejection remained relatively high (99.9%) for both configurations across all tested conditions. The findings revealed that acidification trends caused by MgSO₄ were configuration-dependent, where the parallel setup-controlled rate of pH collapse. This study presented a novel framework connecting membrane module architecture to mass and heat transfer phenomena, providing a transformative DCMD module configuration design in water desalination. These findings not only provide the critical knowledge gaps in DCMD module configurations but also inform optimisation of MD water desalination to achieve high recovery and stable operation conditions under realistic brine composition. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

With the purpose of obtaining synthetic materials from other natural sources for industrial and technological applications, a thermal alteration study was carried out with commercial vermiculites of different purity and origin. For this objective, samples were subjected to 1000 °C in a furnace both at ambient and reduced (N₂/Ar) atmospheres. The thermal behavior and physicochemical properties of the different vermiculites were investigated by X-ray diffraction (XRD), thermal analysis (TG and DTG), and scanning electron microscopy (SEM), and their textural parameters were analyzed by BET treatment. The transformations undergone by the investigated commercial vermiculites subjected to heating treatments caused textural and structural changes in them. There was a decrease in the specific surface area, adsorption capacity, and pore volume values for the samples treated with in situ heating at 1000 °C, both at ambient and reduced atmospheres, and the samples were treated with ex situ abrupt heating at 1000 °C at ambient conditions. There was a decrease in the specific surface area, adsorption capacity, and pore volume values for the samples treated with in situ heating at 1000 °C, both in ambient and reduced atmospheres, which was not observed in the samples treated with an ex situ abrupt heating at 1000 °C at ambient conditions. This corroborated with our findings that the expansion in the first type of thermal treatment produced less separation of the exfoliation sheets than the expansion in the second type of thermal treatment. These textural changes, together with the structural ones, could play a fundamental role in the choice of industrial and technological applications for which these materials could be used. Full article

The mechanical characteristics and mechanisms of rock failure involve complex rock mass mechanics problems involving parameters such as energy concentration, storage, dissipation, and release. Therefore, it is important to select appropriate monitoring technologies to carry out relevant research. Fortunately, infrared thermal imaging monitoring technology has obvious advantages in the experimental study of rock failure processes and energy dissipation and release characteristics under load damage. Therefore, it is necessary to establish the theoretical relationship between the strain energy and infrared radiation information of sandstone and to reveal its fracture energy dissipation and disaster mechanism. In this study, an MTS electro-hydraulic servo press was used to carry out uniaxial loading experiments on sandstone. The characteristics of dissipated energy, elastic energy, and infrared radiation during the damage process of sandstone were studied using infrared thermal imaging technology. The results show that (1) the transition of sandstone loading from one stable state to another occurs in the form of an abrupt change. This sudden change is characterized by the simultaneous occurrence of elastic energy release, dissipative energy surging, and infrared radiation count (IRC) surging, and it has the characteristics of a short duration and large amplitude variation. (2) With the increase in the elastic energy variation, the surge in the IRC of sandstone samples presents three different development stages, namely fluctuation (stage Ⅰ), steady rise (stage Ⅱ), and rapid rise (stage Ⅲ). (3) The more obvious the surge in the IRC, the greater the degree of local damage of the sandstone and the greater the range of the corresponding elastic energy change (or dissipation energy change). (4) A method of sandstone microcrack location and propagation pattern recognition based on infrared thermal imaging technology is proposed. This method can dynamically generate the distribution nephograph of tension-shear microcracks of the bearing rock and accurately evaluate the real-time process of rock damage evolution. Finally, this study can provide a theoretical basis for rock stability, safety monitoring, and early warning. Full article

Fire is one of the natural agents with the greatest impact on the terrestrial ecosystem and plays an important ecological role in a large part of the terrestrial surface. Remote sensing is an important technique applied in mapping and monitoring changes in forest landscapes affected by fires. This study presents a spectral separability analysis for the detection of burned areas using Landsat-8 OLI/TIRS images in the context of fires that occurred in different biomes of Brazil (dry ecosystem) and Portugal (temperate forest). The research is based on a fusion of spectral indices and automatic classification algorithms scientifically proven to be effective with as little human interaction as possible. The separability index (M) and the Reed–Xiaoli automatic anomaly detection classifier (RXD) allowed the evaluation of the spectral separability and the thematic accuracy of the burned areas for the different spectral indices tested (Burn Area Index (BAI), Normalized Burn Ratio (NBR), Mid-Infrared Burn Index (MIRBI), Normalized Burn Ratio 2 (NBR2), Normalized Burned Index (NBI), and Normalized Burn Ratio Thermal (NBRT)). The analysis parameters were based on spatial dispersion with validation data, commission error (CE), omission error (OE), and the Sørensen–Dice coefficient (DC). The results indicated that the indices based exclusively on the SWIR1 and SWIR2 bands showed a high degree of separability and were more suitable for detecting burned areas, although it was observed that the characteristics of the soil affected the performance of the indices. The classification method based on bitemporal anomalous changes using the RXD anomaly proved to be effective in increasing the burned area in terms of temporal alteration and performing unsupervised detection without relying on the ground truth. On the other hand, the main limitations of RXD were observed in non-abrupt changes, which is very common in fires with low spectral signal, especially in the context of using Landsat-8 images with a 16-day revisit period. The results obtained in this work were able to provide critical information for fire mapping algorithms and for an accurate post-fire spatial estimation in dry ecosystems and temperate forests. The study presents a new comparative approach to classify burned areas in dry ecosystems and temperate forests with the least possible human interference, thus helping investigations when there is little available data on fires in addition to favoring a reduction in fieldwork and gross errors in the classification of burned areas. Full article

Invar Fe–Ni alloy is a prominent Ni steel alloy with a low coefficient of thermal expansion around room temperature. We investigate the correlation between magnetic properties and thermal expansion in cold-drawn Fe–36Ni wires with different heat treatment conditions, where the annealing parameters with furnace cooling (cooling from the annealing temperature of 300, 400, 500, 600, 700, 800, 900, and 1000 °C) are used. The variation trend of magnetic properties is consistent with that of thermal expansion for all samples, where the maximum appears at 600 °C -treated sample and 400 °C shows the minimum. The domain size and the area of domain walls determine the total energy of the domain wall, and the total energy directly determines the size of magnetostriction, which is closely related to the coefficient of thermal expansion. Also, the differential thermal analysis (DTA) shows endothermic and exothermic reactions represent crystalline transitions, which could possibly cause the abrupt change of magnetic properties and thermal expansion coefficient of materials. The results indicate that there is a certain relation between thermal expansion and magnetic properties. Besides the fundamental significance, our work provides an Invar alloy with a low coefficient of thermal expansion for practical use. Full article

Hydrological cycle is sensitively affected by climatic variation and human activity. Taking the upper- and middle-stream of the Weihe River in western China as an example, using multiple meteorological and hydrological elements, as well as land-use/land-cover change (LUCC) data, we constructed a sensitivity model of runoff to climatic elements and human activities based on the hydro-thermal coupling equilibrium equation, while a cumulative slope was used to establish a comprehensive estimation model for the contributions of climatic variation and human activities to the changes of runoff. The results showed that the above function model established could be well applied to quantitatively study the elasticity of runoff’s response to climatic variation and human activities. It was found that the annual average precipitation, evaporation, wind velocity, sunshine hours, relative humidity and runoff showed decreasing trends and that temperature increased. While in the hydrological cycle, precipitation and relative humidity had a non-linear positive driving effect on runoff, while temperature, evaporation, sunshine hours, wind velocity, and land-use/land-cover change (LUCC) have non-linearly negatively driven the variation of runoff. Moreover, runoff has a strong sensitive response to precipitation, evaporation and LUCC. In areas with strong human activities, the sensitivity of runoff to climatic change was decreasing, and runoff has a greater elastic response to underlying surface parameters. In addition, the analysis showed that the abrupt years of climate and runoff changes in the Weihe River Basin were 1970, 1985 and 1993. Before 1985, the contribution rate of climatic variation to runoff was 68.3%, being greater than that of human activities to runoff, and then the contribution rates of human activities to runoff reached 75.1%. The impact of natural climate on runoff was weakened, and the effect of human activities on runoff reduction increased. Under 30 hypothetical climatic scenarios, the evaluation of runoff in the future showed that the runoff in the Weihe River Basin will be greatly reduced, and the reduction will be more significant during the flood season. Comparing the geographically fragile environments and intense human activities, it was believed that climatic variation had a dramatic effect on driving the water cycle of precipitation and evaporation and affected regional water balance and water distribution, while human activities had driven the hydrological processes of the underlying surface, thus becoming the main factors in the reduction of runoff. This study provided scientific tools for regional climate change and water resources assessment. Full article

Temperature response of double network (DN) hydrogels composed of thermoresponsive poly(N,N′-diethylacrylamide) (PDEAAm) and hydrophilic polyacrylamide (PAAm) or poly(N,N′-dimethylacrylamide) (PDMAAm) was studied by a combination of swelling measurements, differential scanning calorimetry (DSC) and ¹H NMR and UV-Vis spectroscopies. Presence of the second hydrophilic network in DN hydrogels influenced their thermal sensitivity significantly. DN hydrogels show less intensive changes in deswelling, smaller enthalpy, and entropy changes connected with phase transition and broader temperature interval of the transition than the single network (SN) hydrogels. Above the transition, the DN hydrogels contain significantly more permanently bound water in comparison with SN hydrogels due to interaction of water with the hydrophilic component. Unlike swelling and DSC experiments, a rather abrupt transition was revealed from temperature-dependent NMR spectra. Release study showed that model methylene blue molecules are released from SN and DN hydrogels within different time scale. New thermodynamical model of deswelling behaviour based on the approach of the van’t Hoff analysis was developed. The model allows to determine thermodynamic parameters connected with temperature-induced volume transition, such as the standard change of enthalpy and entropy and critical temperatures and characterize the structurally different states of water. Full article

Shrinkage and warping of additive manufacturing (AM) parts are two critical issues that adversely influence the dimensional accuracy especially in powder bed fusion processes such as selective laser sintering (SLS). Powder fusion, material solidification, and recrystallization are the key stages causing volumetric changes of polymeric materials during the abrupt heating–cooling process. In this work, the mechanisms of shrinkage and warping of semi-crystalline polyamide (PA) 12 in SLS are well investigated. Heat-transfer and thermo-mechanical models are established to predict the process-dependent shrinkage and warping. The influence of raw material- and laser-related parameters are considered in the heat-transfer and thermo-mechanical models. Such models are established considering the natural thermal gradient and dynamic recrystallization, which induce internal strain and volumetric change. Moreover, an experimental design via orthogonal approach is introduced to validate the feasibility and accuracy of the proposed models. Finally, the quantitative relationships of process parameters with product shrinkage and warping are established; the dimensional accuracy in part-scale can be well predicted and validated with printed parts in a real experiment. Full article

A new method to solve thermal conjugacy problems is presented for layered models with a thermal conductivity jump at their boundaries. The purpose of this method is to approximate the inverse thermal conductivity coefficient, which has breaks, by using a combination of step functions. A generalized continuous operator is constructed in a continuous space of piecewise–homogeneous media. We obtained an analytical solution for the stationary problem of heat conjugacy in the layered model with finite thickness and with Dirichlet–Neumann conditions at the external boundaries. An algorithm was constructed for downward continuation of the heat flux to depths that correspond to the top of the mantle layer. The advantages of this method are illustrated by testing the crustal seismic, gravity and geothermal data of a study area in the Urals and neighboring regions of Russia. We examined statistical relations between density and thermal parameters and determined heat flux components for the crust and the mantle. The method enables a downward continuation of the heat flux to the base of the upper mantle and allows us to determine the thermal effects of the lateral and vertical features of deep tectonic structures. Full article

This article is devoted to the geology of titanium-rich varieties of the Petyayan-Vara rare-earth dolomitic carbonatites in Vuoriyarvi, Northwest Russia. Analogues of these varieties are present in many carbonatite complexes. The aim of this study was to investigate the behavior of high field strength elements during the late stages of carbonatite formation. We conducted a multilateral study of titanium- and niobium-bearing minerals, including a petrographic study, Raman spectroscopy, microprobe determination of chemical composition, and electron backscatter diffraction. Three TiO₂-polymorphs (anatase, brookite and rutile) and three pyrochlore group members (hydroxycalcio-, fluorcalcio-, and kenoplumbopyrochlore) were found to coexist in the studied rocks. The formation of these minerals occurred in several stages. First, Nb-poor Ti-oxides were formed in the fluid-permeable zones. The overprinting of this assemblage by residual fluids led to the generation of Nb-rich brookite (the main niobium concentrator in the Petyayan-Vara) and minerals of the pyrochlore group. This process also caused niobium enrichment with of early generations of Ti oxides. Our results indicate abrupt changes in the physicochemical parameters at the late hydro (carbo) thermal stage of the carbonatite formation and high migration capacity of Ti and Nb under these conditions. The metasomatism was accompanied by the separation of these elements. Full article

Optical microscopes and nanoscale probes (AFM, optical tweezers, etc.) afford researchers tools capable of quantitatively exploring how molecules interact with one another in live cells. The analysis of in vivo single-molecule experimental data faces numerous challenges due to the complex, crowded, and time changing environments associated with live cells. Fluctuations and spatially varying systematic forces experienced by molecules change over time; these changes are obscured by “measurement noise” introduced by the experimental probe monitoring the system. In this article, we demonstrate how the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS) of Fox et al. [IEEE Transactions on Signal Processing 59] can be used to detect both subtle and abrupt state changes in time series containing “thermal” and “measurement” noise. The approach accounts for temporal dependencies induced by random and “systematic overdamped” forces. The technique does not require one to subjectively select the number of “hidden states” underlying a trajectory in an a priori fashion. The number of hidden states is simultaneously inferred along with change points and parameters characterizing molecular motion in a data-driven fashion. We use large scale simulations to study and compare the new approach to state-of-the-art Hidden Markov Modeling techniques. Simulations mimicking single particle tracking (SPT) experiments are the focus of this study. Full article