Transient Analysis Research Articles

Physical Exercise to Redynamize Interoception in Substance use Disorders.

Physical exercise is considered a promising medication-free and cost-effective adjunct treatment for substance use disorders (SUD). Nevertheless, evidence regarding the effectiveness of these interventions is currently limited, thereby signaling the need to better understand the mechanisms underlying their impact on SUD, in order to reframe and optimize them. Here we advance that physical exercise could be re-conceptualized as an "interoception booster", namely as a way to help people with SUD to better decode and interpret bodily-related signals associated with transient states of homeostatic imbalances that usually trigger consumption. We first discuss how mismatches between current and desired bodily states influence the formation of reward-seeking states in SUD, in light of the insular cortex brain networks. Next, we detail effort perception during physical exercise and discuss how it can be used as a relevant framework for re-dynamizing interoception in SUD. We conclude by providing perspectives and methodological considerations for applying the proposed approach to mixed-design neurocognitive research on SUD.

X-ray computed tomography tracking of the calcium chloride hexahydrate crystallisation process

The research conducted on phase change materials (PCMs) for latent thermal energy storages (LTESs) is continuously growing in terms of publications, highlighting the importance of this topic. In fact, PCMs present many advantages that could help the energy transition and reduce CO2 emissions, by enhancing the performance of existing systems and better exploiting renewable energy. Therefore, it is of crucial interest to develop new and reliable methods to control LTES. Differently from sensible thermal energy storages, in LTESs the stored thermal energy is not proportional to the temperature. To really have an insight into the level of charge of these storages, it is important to know the liquid fraction, i.e., the amount of the liquid phase with respect to the whole amount of PCM. X-ray computed tomography (XCT) is a technology that allows to non-intrusively “look inside” the materials. In the current study, it was used to analyse the calcium chloride hexahydrate crystallization. This transient process of calcium chloride hexahydrate was tracked with a sequence of XCT scans, one every 6 minutes, resulting in 3D image stacks that were processed to obtain the volumetric liquid fraction evolution over time. Repeatability tests were run to evaluate the reliability of the XCT technique and the volumetric liquid fraction data was used to validate a numerical model developed within ANSYS Fluent framework. XCT offers great opportunities to study the heat and mass transfer mechanisms underlying the main issues of phase change materials, like, for example, supercooling and salt hydrate segregation.

LPT rotor speed after low-pressure shaft failure

When designing engine safety and compliance with airworthiness regulations, it is important to determine the variation of rotor rotational speed and other parameters of aero-engine under shaft failure scenarios. In this paper, a transient process simulation model is established using the component method for a high bypass ratio two-shaft direct-drive turbofan engine. It helps analyze the response of engine rotor speed and key temperature parameters after the failure of the low-pressure shaft, the influence of the fuel supply, low-pressure turbine efficiency, and rotor resistance torque on the response of the parameters. The results demonstrate that the sudden increase of the low-pressure shaft speed at the turbine end after the failure of the low-pressure shaft is the most important factor affecting the engine safety design. The fuel supply, LPT efficiency, and resistance torque have significant effects on this sudden increase in speed.

Transient analysis of growth/decay in materials utilizing a digital exponential peeling method

AbstractAn algorithm is proposed to implement digital peeling to determine dominant time constants of an exponential transient process. The method is simpler to implement and reduces computational time to a large extent in comparison to other techniques widely used. Apart from a synthetic test function, the algorithm has been implemented on reported experimental transient decay curves of Cs2HfCl6 (CHC) single crystal scintillation to verify its efficacy. Finally, drain current detrapping transients of unpassivated AlGaN/GaN high electron mobility transistors (HEMTs) are analyzed to determine the trap energy levels and concentrations. The validation of this digital peeling technique is also carried out by comparing with conventional method of time constant extraction from HEMT current transients. The extracted exponentials from the transient data efficiently fits well with the experimental data and can be extensively used for transient analysis. The digital peeling technique has wide applicability and can be used to analyze all exponential processes which occur in all domains of science.

Applications of Asymptotic Solutions of the Diffusivity Equation to Infinite Acting Pressure Transient Analysis

Summary Understanding how pressure propagates in a reservoir is fundamental to the interpretation of pressure and rate transient measurements at a well. Unconventional reservoirs provide unique technical challenges as the simple geometries and flow regimes [wellbore storage (WBS) and radial, linear, spherical, and boundary-dominated flow] applied in well test analysis are now replaced by nonideal flow patterns due to complex multistage fracture completions, nonplanar fractures, and the interaction of flow with the reservoir heterogeneity. In this paper, we introduce an asymptotic solution technique for the diffusivity equation applied to pressure transient analysis (PTA), in which the 3D depletion geometry is mapped to an equivalent 1D streamtube. This allows the potentially complex pressure depletion geometry within the reservoir to be treated as the primary unknown in an interpretation, compared with the usual method of interpretation in which the depletion geometry is assumed and parameters of the formation and well are the unknown properties. The construction is based upon the solution to the Eikonal equation, derived from the diffusivity equation in heterogeneous reservoirs. We develop a Green’s function that provides analytic solutions to the pressure transient equations for which the geometry of the flow pattern is abstracted from the transient solution. The analytic formulation provides an explicit solution for many well test pressure transient characteristics such as the well test semi-log pressure derivative (WTD), the depth of investigation (DOI), and the stabilized zone (SZ) (or dynamic drainage area), with new definitions for the limit of detectability (LOD), the transient drainage volume, and the pseudosteady-state (PSS) limit. Generalizations of the Green’s function approach to bounded reservoirs are possible (Wang et al. 2017) but are beyond the scope of the current study. We validate our approach against well-known PTA solutions solved using the Laplace transform, including pressure transients with WBS and skin. Our study concludes with a discussion of applications to unconventional reservoir performance analysis for which reference solutions do not otherwise exist.

Structural Behaviour and Strength Evaluation of a Venetian Church through Finite-Element Analysis

The evaluation of the structural behaviour of a masonry Venetian church with a pointed barrel vault is presented in this paper through an analysis following the necessary steps of a monument study. With a detailed geometric model and material estimation, the finite-element method is used to investigate the influence of specific structural parts of the structure, like masonry buttresses and wall connections, on the structural behaviour. The operational modal analysis is used to identify the structure dynamically. The comparison of the eigenfrequencies, which are estimated by in situ measurements and finite-element modal analysis, is used to perform a model identification. The response spectrum analysis, the static analysis after the subsistence of some parts following strengthening proposals, and the transient analysis of specific seismic excitations are used for the evaluation of the structural behaviour. The purpose of the work is to highlight the need for an interdisciplinary approach to the study of a monumental complex structure, regardless of its scale. The coexistence of structural elements of different stiffnesses, such as vaults, elongated walls, buttresses, transverse walls with pediment and belfry, as well as the concha, affects the mechanical behaviour and the pathology of the structure, which is difficult to study with simplifying models. From the analysis, it is concluded that subsidence problems, combined with seismic actions, lead to the cracking of the masonry, while the existence of buttresses limits the extension of the damage and contributes to the stabilization of the structure.

A physics-driven and machine learning-based digital twinning approach to transient thermal systems

Purpose In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system. Design/methodology/approach To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop. Findings The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems. Originality/value The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

Thermal performance evaluation of hempcrete masonry walls for energy storage in cold weather

During winter, buildings tend to consume a lot of energy for heating due to insufficient insulation of their envelopes. To address this issue, this study explores the use of materials with low thermal conductivity and high specific heat capacity, such as hempcrete, to minimize energy losses through the building envelope. The study suggests optimizing hempcrete components to enhance their thermal properties and evaluates the stored and lost thermal energy to improve the overall thermal performance of building envelopes. Twenty-five hempcretes are experimentally produced and thermally characterized. The thermal assessment also includes some hemp concretes from the literature for comparison purposes. ANSYS Fluent software is used to model the hempcrete walls in a transient state in terms of thermal storage capacity and losses in cold weather (e.g., −20 °C). Results show that stored energy is mainly affected by the product of hempcrete ρ and Cp values, while lost energy depends on thermal conductivity and diffusivity. The highest stored energy over 24 h is observed at 1.91 and 5.54 MJ/m2 for HC3 (literature) and AAFA-NaOH (present study), respectively, with a difference of 190 %. Further, the lowest values for lost energy are 0.44 and 0.42 MJ/m2 for HC2 (literature) and S2-CA (present study), respectively. To combine both stored energy and lost energy together, HC2 shows the best performance for the literature walls with lost energy of 0.44 MJ/m2 and stored energy of 1.82 MJ/m2; however, the present S2-CA hempcrete has lower lost energy at 0.42 MJ/m2 and higher stored energy at 3.07 MJ/m2. Additionally, a present C + Li + 30 %SF hempcrete has a similar lost energy of 0.46 MJ/m2 but a higher stored energy of 3.36 MJ/m2. The increasing hemp content has been noticed to increase stored energy by up to 86 % and reduce lost energy by 14.8 %.

TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

The motor drives for aqua farms and large-scale irrigation system needs a reliable electric drive, which requires the continuous power supply and efficient control. However, the rural single phase power supply is frequently interrupted. Renewable assistance would improve the availability of supply and heuristic control approach improves robustness in control. This paper presents a three phase induction motor drive fed from single phase electric grid with assistance from PV and battery energy storage. TS- fuzzy based direct torque control is employed for robust control during load changes, and the topology, component modelling, front-end converter control, PV interface DC–DC converter control, and inverter control are presented. MATLAB/Simulink is used to simulate the proposed drive system. The performance of the proposed system is validated using simulation data for both steady-state and transient states.

An Experimental Method to Capture the Thermal Conductivity Coefficient of Fine-Grained Concretes during Transition from Liquid to Solid.

During the transition from liquid to solid, the thermal conductivity coefficient λ of concrete decreases. Although λ of hardened concrete is well investigated, there is limited research on the transition from liquid to solid and how it depends on hydration. Currently, only simplified qualitative approaches exist for the liquid state and the transient process. An experimental method is not available. For this purpose, a test rig is designed to experimentally capture the evolution of λ for fine-grain concretes during transition. The performance of the test setup is evaluated on a characteristic high-performance concrete (HPC). The results are compared to theoretical predictions from the literature. The developed test rig is mapped in a digital twin to investigate extended boundary conditions, such as different heat sources and temperatures of the experimental setup. It allows the experiment to be repeated and optimized for different setups with little effort. The test principle is as follows: A liquid concrete sample is heated through a controlled external source, while the transient temperature distribution over the height is measured with a fiber optic sensor. The thermal conductivity is derived from the heat flux induced and the temperature distribution over an evaluation length. Experiments show that λ in the liquid state is approximately 1.4 times greater than in the solid state and exponentially decreases for the transient process. Numerical results on the digital twin indicate that the robustness of the results increases with the temperature of the heat source. Moreover, the derivation in λ turns out to be strongly dependent on the evaluation length. A length of three times the maximum grain diameter is recommended.

Transient Zn2+ deficiency induces replication stress and compromises daughter cell proliferation

Cells must replicate their genome quickly and accurately, and they require metabolites and cofactors to do so. Ionic zinc (Zn2+) is an essential micronutrient that is required for hundreds of cellular processes, including DNA synthesis and adequate proliferation. Deficiency in this micronutrient impairs DNA synthesis and inhibits proliferation, but the mechanism is unknown. Using fluorescent reporters to track single cells via long-term live-cell imaging, we find that Zn2+ is required at the G1/S transition and during S phase for timely completion of S phase. A short pulse of Zn2+ deficiency impairs DNA synthesis and increases markers of replication stress. These markers of replication stress are reversed upon resupply of Zn2+. Finally, we find that if Zn2+ is chelated during the mother cell's S phase, daughter cells enter a transient quiescent state, maintained by sustained expression of p21, which disappears upon reentry into the cell cycle. In summary, short pulses of mild Zn2+ deficiency in S phase specifically induce replication stress, which causes downstream proliferation impairments in daughter cells.

Single-cell transcriptomics: background, technologies, applications, and challenges.

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 1: Event detection for cryoseismology

Abstract. Cryoseismology is a powerful toolset for progressing the understanding of the structure and dynamics of glaciers and ice sheets. It can enable the detection of hidden processes such as brittle fracture, basal sliding, transient hydrological processes, and calving. Addressing the challenge of detecting signals from many different processes, we present a novel approach for the semi-automated detection of events and event-like noise, which is well-suited for use as Part 1 of a workflow where unsupervised machine learning will be used as Part 2 (Latto et al., 2024) to facilitate the main reconnaissance of diverse detected event types. Implemented in the open-source and widely used ObsPy Python package, the multi-STA/LTA algorithm constructs a hybrid characteristic function from a set of short-term average (sta)–long-term average (lta) pairs (refer to Sect. 2 in the main text for an explanation of how uppercase and lowercase STA/sta and LTA/lta abbreviations are differentiated). We apply the algorithm to data from a seismic array deployed on the Whillans Ice Stream (WIS) in West Antarctica (austral summer 2010–2011) to form a “catch-all” catalogue of events and event-like noise. The new algorithm compares favorably with standard approaches, yielding a diversity of seismic events, including all previously identified stick-slip events (Pratt et al., 2014), teleseisms, and other noise-type signals. In terms of a catalogue overview, we investigate a partial association of seismicity with the tidal cycle and a slight association with ice temperature changes of the Antarctic summer. The new algorithm and workflow will assist in the comparison of different glacier environments using seismology, the identification of process change over time, and the targeting of possible subsequent high-resolution studies.

Investigation on the flow and induced-noise mechanism during the transient start-up process of a mixed-flow pump

PurposeThis study aims to investigate the noise-inducing characteristics during the start-up process of a mixed-flow pump and the impact of different start-up schemes on pump noise.Design/methodology/approachThis study conducted numerical simulations on the mixed-flow pump under different start-up schemes and investigated the flow characteristics and noise distribution under these schemes.FindingsThe results reveal that the dipole noise is mainly caused by pressure fluctuations, while the quadrupole noise is mainly generated by the generation, development and breakdown of vortices. Additionally, the noise evolution characteristics during the start-up process of the mixed-flow pump can be divided into the initial stage, stable growth stage, impulse stage and stable operation stage.Originality/valueThe findings of this study can provide a theoretical basis for the selection of start-up schemes for mixed-flow pumps, reducing flow noise and improving the operational stability of mixed-flow pumps.

Viscoelastic modelling and analysis of two-dimensional woven CNT-based multiscale fibre reinforced composite material system

Carbon nanotube (CNT) has fostered research as a promising nanomaterial for a variety of applications due to its exceptional mechanical, optical, and electrical characteristics. The present article proposes a novel and comprehensive micromechanical framework to assess the viscoelastic properties of a multiscale CNT-reinforced two-dimensional (2D) woven hybrid composite. It also focuses on demonstrating the utilisation of the proposed micromechanics in the dynamic analysis of shell structure. First, the detailed constructional attributes of the proposed trans-scale composite material system are described in detail. Then, according to the nature of the constructional feature, mathematical modelling of each constituent phase or building block’s material properties is established to evaluate the homogenised viscoelastic properties of the proposed composite material system. To highlight the novelty of this study, the viscoelastic characteristics of the modified matrix are developed using the micromechanics method of Mori–Tanaka (MT) in combination with the weak viscoelastic interphase (WI) theory. In the entire micromechanical framework, the CNTs are considered to be randomly oriented. The strength of the material (SOM) approach is used to establish mathematical frameworks for the viscoelastic characteristics of yarns, whereas the unit cell method (UCM) is used to determine the viscoelastic properties of the representative unit cell (RUC). Different numerical results have been obtained by varying the CNT composition, interface conditions, agglomeration, carbon fibre volume percentage, excitation frequency, and temperature. The influences of geometrical parameters like yarn thickness, width, and the gap length to yarn width ratio on the viscoelasticity of such composite material systems are also explored. The current study also addresses the issue of resultant anisotropic viscoelastic properties due to the use of dissimilar yarn thickness. The results of this micromechanical analysis provide valuable insights into the viscoelastic properties of the proposed composite material system and suggest its potential applications in vibration damping. To demonstrate the application of developed novel micromechanics in vibration analysis, as one of the main contributions, comprehensive numerical experiments are conducted on a shell panel. The results show a significant reduction in vibration amplitudes compared to traditional composite materials in the frequency response and transient response analyses. To focus on the aspect of micromechanical behaviour on dynamic response and for the purpose of brevity, only linear strain displacement relationships are considered for dynamic analysis. These insights could inform future research and development in the field of composite materials.

A methodology for the optimal placement of conformal cooling channels in injection molds: 2D transient heat transfer analysis

A methodology for the optimal placement of conformal cooling channels in injection molds: 2D transient heat transfer analysis

Aiming at the valorization of CO2 through its capture by simply extruded high cell-density coal honeycombs

Integral coal honeycomb monoliths were easily prepared achieving the cell densities typical of commercial cordierites through extrusion plus physical activation. Different techniques such as volumetric adsorption, TGA, TPD and transient kinetic analysis were employed to study their interaction with CO2 at different temperatures (35–100 °C) and under both static and dynamic atmosphere. The CO2 capture capacity resulted to be 0.95 mmol/g at 35 °C, much higher than that of previously studied clay honeycomb adsorbents. The CO2 uptake exhibited fast second order kinetics, and a wide operative window for a highly efficient CO2 removal was found. Moreover, due to a weak interaction, most CO2 adsorbed could be released at 110 °C, what allows minimizing the costs related to controlled regeneration if ones wants to reuse the captured CO2 but at the same time prevents from desorption when this is undesirable. Treatment of the coal honeycomb monolith with a 1:1 CO2+CH4-containing stream revealed, through gas chromatography analysis, the conversion into syngas at relatively low temperatures (50% at 750 °C) in spite of the metal-free character of the monolith. Moreover, this activity reached 90% and remained quite stable for at least 12 h at 900 °C. These results demonstrate the potential of preparing honeycomb monoliths from coal as a strategy to diversify the uses of this abundant natural resource and as an alternative in the field of CO2 capture and valorization.

Simulation analysis of thermal insulation performance of diesel engine piston based on PEO and La2Zr2O7 thermal barrier coating

In this research, we explored the application of ‘thermal swing’ thermal barrier coatings (TBCs) in diesel engines, aiming to surpass the performance of conventional TBCs. Traditional TBCs often suffer from limitations like consistently high surface temperatures and a delayed response to sudden variations in cylinder temperatures, which adversely impact engine efficiency. To overcome these challenges, plasma electrolytic oxidation (PEO) technology was employed to engineer TBCs with the sought-after ‘thermal swing’ feature. Comparative simulations were conducted to assess the thermal characteristics of PEO coatings on pistons, in contrast to standard La2Zr2O7 coatings. The steady-state thermal analysis revealed that PEO coatings maintained a lower peak temperature compared to La2Zr2O7 coatings under similar thermal insulation conditions, indicating a superior ability of the PEO coatings in heat dissipation and in sustaining lower surface temperatures.In the transient thermal analysis, focusing on temporal temperature variations, the PEO coatings exhibited a markedly quicker and more robust response to cylinder temperature fluctuations. This indicates that PEO coatings are highly effective in adapting swiftly to temperature changes, thereby contributing to enhanced engine performance. Additionally, the PEO coating demonstrated a notable reduction in the end temperature (TE), which is crucial for mitigating the heating effect on intake gas, in comparison to La2Zr2O7 coatings with equivalent thermal insulation properties. However, it was observed that this advantage significantly decreased when the PEO coating thickness surpassed 0.3 mm. Drawing from these observations, it is concluded that PEO coatings hold several thermal advantages over La2Zr2O7 coatings, particularly in terms of thermal load management and responsiveness to in-cylinder temperature shifts. These benefits are most pronounced when the PEO coating maintains a thickness below 0.3 mm.

A Novel Adaptive Third-Order Continuous Super-Twisting Controller of a Five Phase Permanent Magnet Synchronous Wind Generator

The aim of this research is to enhance the control of a Wind Energy Generating System (WEGS) incorporating a Five-phase Permanent Magnet Synchronous Generator (5 ph-PMSG) and addressing operational challenges in the presence of disturbances. The commonly employed Second-Order Super-Twisting Controller (SOSTC), with constant gains, has limitations, including uncertainties, significant transient state errors, and chattering effects, hindering its practical applicability. To overcome these drawbacks, the study proposes the application of an Adaptive Third-Order Continuous Super-Twisting Control (ATOCSTC). This novel approach integrates a third-order sliding mode surface, a smoothly continuous switching control term, and an adaptation law. Unlike the conventional SOSTC using discontinuous “sign” functions, ATOCSTC dynamically adjusts gains using tangent hyperbolic functions, providing a continuous and effective control mechanism. Comparative analysis with the conventional SOSTC under various disturbances such as wind speed fluctuations, parameter variations, and Grid Voltage Sag (GVS), reveals significant improvements with ATOCSTC. Notably, ATOCSTC leads to a 75% reduction in power ripples for grid active power and a 40.38% reduction for grid reactive power. These findings underscore the superior performances obtained with the proposed ATOCSTC in WEGS.

A case study for optimization of power system load flow analysis using ETAP software

This research report explores the optimization of power system load current analysis by integrating Electrical Transient Analyzer Program (ETAP) software and Single Line Diagram (SLD) representation. Load current analysis is essential for the reliable and efficient operation of power grids, and the use of advanced software tools such as ETAP offers significant opportunities to improve analysis capabilities. The integration of SLD with ETAP enables more intuitive and comprehensive visualization of energy system elements and their connections, improving the modelling and analysis process. The article presents a case study that demonstrates the practical application of this integrated approach using a typical power system model to estimate load current characteristics under various operating conditions. The methodology involves building a powerful system model in ETAP and includes SLD representations to improve system visualization and analysis. The system simulation experiments evaluate the performance and accuracy of the integrated ETAPSLD approach, focusing on key parameters such as voltage profiles, current flows, enabling more efficient load current analysis and providing valuable information for power system engineers and operators. Overall, this study contributes to the field of energy system analysis by using advanced software tools for advanced modelling and optimization.