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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dynamic modelling and control strategy of a temperature-driven metal hydride cooling system for buildings

A temperature-driven coupled metal hydride (MH) based thermal energy storage (TES) system can allow to shave and shift the peak energy demand in buildings. The high energy density and long-term (seasonal) energy storage capability are its major advantages over other energy storage methods. The dynamic nature of the MH operation, however, requires controlled hydrogen transfer between the coupled MHs at a rate needed to meet the building's transient load. While temperature-driven MH systems are studied in the literature, their application in buildings and control are scarcely reported. Here, this paper presents a control-based dynamic modeling of the temperature-driven coupled MH-TES system for building cooling applications. The dynamic model is developed in MATLAB(R) Simulink environment, considering the thermodynamic and kinetic behaviors of the MH systems. Based on a preliminary analysis of a property database of over 337 hydrides, we select around 1600 MH pairs suitable for building cooling applications. Each of these MH pairs is studied for their performance using the dynamic model, and among all, Zr 0.76 Ti 0.24 Ni 1.16 Mn 0.63 V 0.14 Fe 0.18 -Ti 0.85 Zr 0.15 Cr 1.2 Mn 0.8 MH pair showed fast dynamics along with high coefficient of performance (COP) of 0.71. A parametric investigation is performed on this MH pair to understand the effect of operating temperatures. Finally, three proportional-integral (PI) feedback controllers are investigated to regulate the temperature, pressure and mass exchange between the coupled MH pairs. The developed PI controller is sufficiently capable of rejecting the signal noise from the hydrogen flow and internal heat exchange processes with root mean square error of 5.78 W between reference and actual cooling load.

08 HYDROGEN↗
DOE OSTI2020

Estimating Sediment Settling Velocities from a Theoretically Guided Data-Driven Approach

Sediment settling velocities are commonly estimated from analytical or process-based approaches. These approaches have theoretical constraints due to the incompletely resolved settling physics. A parametric data-driven approach was recently proposed without theoretical constraints, but it is limited by its mathematical assumptions. To overcome these limitations, here we apply a machine learning algorithm to an aggregated sediment settling experimental database and develops a nonparametric data-driven model to estimate the noncohesive sediment settling velocity in water. A cross-comparison against five process-based equations and a parametric data-driven equation demonstrates the higher accuracy and better consistency of the new model in estimating sediment settling velocities under various physical regimes. The new model also shows an easily implemented self-update capability by assimilating theoretical data derived from the process-based equations. The updated model, incorporating experimental and theoretical data of sediment settling processes, further improves the accuracy and reduces the uncertainty in estimating sediment settling velocities. This study demonstrates the capability of machine learning in sediment transport study and illustrates an alternative framework for other hydraulic engineering challenges.

42 ENGINEERING↗
DOE OSTI2025

DFT-based insight into finite-temperature properties of ferroelectric perovskites with lone-pair: the case of CsGeX 3 (X = Cl, Br, I)

Ferroelectrics remain in the focus of scientific attention for decades owing to their fundamental and practical appeal. Recently, ferroelectricity has been demonstrated in semiconducting halide perovskites (Zhang et al 2022 Sci. Adv. 8 eabj5881), offering both a rare combination of ferroelectricity and semiconductivity in the same material and a possible alternative to the prevailing perovskite oxide ferroelectrics. We propose a route to simulating such materials at finite temperatures capable of reproducing key experimental and first-principle data, such as Curie temperature, phase transition sequence, spontaneous polarization, and soft mode frequencies. The key methodological finding is the superior performance of hybrid exchange correlation functionals in parametrization of effective Hamiltonians for ferroelectrics with lone pair. The parametrization for effective Hamiltonians for CsGeX 3 (X = Cl, Br, I) is reported. The application of methodology to study polarization reversal in CsGeX 3 allows for the development of a ‘minimalistic’ model for polarization reversal in ferroelectrics that provides an insight into the mechanisms of polarization reversal and its key features, such as the relationship between the coercive field, temperature, and AC field frequency. Importantly, the model reveals the origin of the well-known and ever-puzzling overestimation of coercive fields in computations. Furthermore, we report a variety of finite-temperature properties of CsGeX 3 ferroelectrics, such as dielectric susceptibility, pyroelectric coefficients, and energy storage density, which reveal that these halide perovskites possess properties comparable to their oxide counterparts. Here, we believe that our work provides significant methodological advancements, deepens fundamental understanding of ferroelectrics, and reveals the potential of halide perovskite ferroelectrics.

effective Hamiltonian↗
DOE OSTI2025

High-dynamic-range quantum sensing of magnons and their dynamics using a superconducting qubit

Magnons, the quanta of collective spin excitations in magnetic materials, may enable functionalities, such as nonreciprocity and transduction in hybrid quantum devices. To assess the potential of such applications, it is necessary to understand magnon dynamics beyond the simple harmonic oscillator regime, where theory predicts effects like population-dependent damping and quantum fluctuations in the form of magnon shot noise. Probing these phenomena requires sensors with high sensitivity and the ability to resolve magnon properties across different excitation regimes. Here, we demonstrate accurate and sensitive detection of magnon population and decay over a wide range of occupation numbers. We use a superconducting qubit to probe magnons in a ferrimagnet over approximately 2000 excitations. Using qubit control and parametrically induced qubit-magnon interactions, we demonstrate few-excitation sensitive detection of magnons with a dynamic range of approximately 30 dB, and are able to accurately resolve their decay with few-ns sensitivity. These capabilities offer a powerful and practical technique for probing magnon dynamics in or beyond the linear regime over a wide range of excitations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A continuum damage approach to spallation and the role of microinertia

Spall failure is of interest due to its prevalence in high strain rate problems in which the spallation is driven by the interaction of release waves. In this article, a porosity-based damage model that includes microinertial effects is used to examine spall failure. The model is successfully calibrated to plate impact-driven experiments and then used to evaluate experimental conditions producing more extreme strain rate conditions, such as those in laser-driven experiments. The incorporation of microinertia allows us to better understand the increase in apparent macroscopic spall strength seen at high strain rates. Correspondingly, we conclude that the incorporation of microinertial effects improves the model’s predictive capabilities. Microinertial effects result in more severe local tensile stresses that affect the damage evolution, and microinertia can play a significant role in the approach to the material’s ideal strength at extreme loading rates. Additionally, a preliminary parametric study is also carried out to investigate the role of microstructural aspects such as nucleation volume fraction and initial pore radius. One counter-intuitive result from the microinertial effects is that, for a given nucleation site volume fraction, having larger initial pore nucleation sites can lead to an improved macroscopic spall strength.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of Conceptual Lead Cartridge Design to Perform Irradiation Experiments in VTR

This paper seeks to introduce the latest design of the Extended Length Test Assembly–Cartridge Lead (ELTA-CL) with associated thermal-hydraulic (TH) assessment and related experiment activities to support the critical component development performed by the ELTA-CL team (Los Alamos National Laboratory, Westinghouse Electric Company, and the University of New Mexico). The goal of the ELTA-CL program is to develop and validate an experimental capability to perform irradiation experiments in the Versatile Test Reactor (VTR) addressing Lead Fast Reactor (LFR) technology gaps, in support of the commercial development of advanced lead-cooled fast reactor concepts. Through a design maturation process and parametric study, a conceptual design is proposed to meet the requirements for material and corrosion testing. Thermal-hydraulic characteristics for the conceptual design at desired operating conditions are assessed with systems-level (one-dimensional) and computational fluid dynamics (three-dimensional) simulations. Along with the conceptual design work, experimental activities for the development of critical components such as the pump and flowmeter are undertaken. From both the modeling study and the experimental results, the design requirements of the Phase 1 ELTA-CL (e.g., 500°C and 2 m/s) are achievable with the current conceptual design. Additional design improvements and safety assessments at both steady-state and transient conditions for the final ELTA-CL design will be pursued.

42 ENGINEERING↗
DOE OSTI2021

Gradient sensing via cell communication

Experimental evidence lends support to the conjecture that cell-to-cell communication plays a role in the gradient sensing of chemical species by certain chains of cells. Models have been formulated to explore this idea. For cells with no identifiable sensing structure, Mugler et al. [Proc. Natl. Acad. Sci. (U.S.A.) 113, E689 (2016)] have defined a particular local excitation, global inhibition (LEGI) model that pits nearest-neighbor communication against local reactions in a noisy environment to suggest how this sensing capability might arise in a physical system. In this study, we generalize the nearest-neighbor communication mechanism in the aforementioned LEGI model in order to explore the extent to which the gradient sensing characteristics depend on the parametrization of the communication itself, as well as on the cell size, the radius of influence of neighboring cells, and the influence of the background noise. Using our generalization and a collection of particular candidate communication models, we find that the precision of gradient sensing is indeed sensitive to the particular communication model, and we derive physical and analytic explanations for these results. The framework established and the associated results should prove useful in understanding the appropriateness of particular cell-to-cell communication models in gradient sensing studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spin-lattice model for cubic crystals

In this work, we present a methodology based on the Néel model to build a classical spin-lattice Hamiltonian for cubic crystals capable of describing magnetic properties induced by the spin-orbit coupling like magnetocrystalline anisotropy and anisotropic magnetostriction, as well as exchange magnetostriction. Taking advantage of the analytical solutions of the Néel model, we derive theoretical expressions for the parametrization of the exchange integrals and Néel dipole and quadrupole terms that link them to the magnetic properties of the material. This approach allows us to build accurate spin-lattice models with the desired magnetoelastic properties. We also explore a possible way to model the volume dependence of magnetic moment based on the Landau energy. This feature allows us to consider the effects of hydrostatic pressure on the saturation magnetization. We apply this method to develop a spin-lattice model for BCC Fe and FCC Ni, and we show that it accurately reproduces the experimental elastic tensor, magnetocrystalline anisotropy under pressure, anisotropic magnetostrictive coefficients, volume magnetostriction, and saturation magnetization under pressure at zero temperature. This work could constitute a step towards large-scale modeling of magnetoelastic phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Feasibility Study for Disposal Control Rod Assemblies Using UNF-ST&DARDS As-Loaded Zion Dual Purpose Cask Models

This report documents an initial evaluation to support future use of disposal control rod assemblies (DCRAs) for post-closure criticality control in dual purpose canisters (DPCs). The work described herein is an extension of previous efforts performed by Walker using inputs generated by the Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNFST&DARDS) for the Zion site DPCs with as-loaded isotopic compositions. The results of this analysis demonstrate that there are multiple pathways to using DCRA for post-closure criticality control. Various configurations of DCRA material, diameter, number of rods per DCRA, and number and location of DCRAs within a DPC were shown to be effective in varying degrees for the set of DPCs analyzed by Walker. Because of the variations in DPC as-loaded isotopic compositions considered in an array of DCRA parametric sweeps, it can be concluded that a DPC-specific methodology is feasible (i.e., a one-size-fits-all approach may not be needed). Instead, the utility program created for this work can be expanded to develop capabilities to provide DPC-specific DCRA arrangements to limit cost and weight and to allow for operational considerations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Numerical investigation of equivalence ratio effects on Flex-Fuel mixing controlled combustion enabled by prechamber ignition

There is interest in adapting renewable and low-carbon intensity fuels to heavy-duty engines to help displace criteria and greenhouse gas emissions associated with diesel combustion. Low-carbon fuels have inherently low cetane numbers and thus pose a significant challenge when considering direct substitution in diesel combustion systems. Use of an actively fueled prechamber as an ignition source to initiate mixing-controlled combustion (PC-MCC) of low-cetane fuels is becoming an attractive combustion mode to alleviate the identified reactivity deficit. This work focuses on the utilization of an active prechamber to facilitate diesel-like combustion of bioethanol-gasoline fuel blends in a heavy-duty engine. Recent results in this emerging technology suggest that ignition quality is uniquely coupled to prechamber equivalence ratio. In this numerical study, the fundamental implications of prechamber equivalence ratio on the ignition performance of direct injected fuels ranging from E10 to E100 are investigated using CONVERGE. Parametric studies of the prechamber operating strategy were assessed at diesel-like conditions to characterize the performance trends relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and achieves diesel-like ignition qualities and combustion processes for all fuels considered under stoichiometric and rich prechamber conditions. To characterize the equivalence ratio trends observed, a novel inflow boundary modeling technique was utilized to prescribe turbulent jets in place of the prechamber where selective speciation of the jet composition was conducted to isolate the ignition contributions of radical and reacting species in lean, stoichiometric, and rich jets. The inflow boundary modeling suggests that excess fuel and combustion intermediates present in jets produced from stratified and fuel-rich prechamber operation promotes higher jet temperatures and as such are superior ignition sources. Relative to a lean prechamber jet, the peak temperature of a reacting jet from a rich prechamber was up to 600 K hotter at fixed distances from the orifice exit. Furthermore, radicals also demonstrated an influence on the ignition process, but the combustion mode was identified to be thermally dominant.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Quantum reservoir computing implementation on coherently coupled quantum oscillators

Quantum reservoir computing is a promising approach for quantum neural networks, capable of solving hard learning tasks on both classical and quantum input data. However, current approaches with qubits suffer from limited connectivity. We propose an implementation for quantum reservoir that obtains a large number of densely connected neurons by using parametrically coupled quantum oscillators instead of physically coupled qubits. We analyze a specific hardware implementation based on superconducting circuits: with just two coupled quantum oscillators, we create a quantum reservoir comprising up to 81 neurons. We obtain state-of-the-art accuracy of 99% on benchmark tasks that otherwise require at least 24 classical oscillators to be solved. Our results give the coupling and dissipation requirements in the system and show how they affect the performance of the quantum reservoir. Beyond quantum reservoir computing, the use of parametrically coupled bosonic modes holds promise for realizing large quantum neural network architectures, with billions of neurons implemented with only 10 coupled quantum oscillators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multibody for Everybody (M4E) - A Linearization Approach to Enable Frequency Domain Analysis, Time Integration and Control Co-Design

1.1 Background/Objectives: Marine energy represents a promising yet underexploited source of power. To increase the harvested power, significant efforts have been made to improve wave energy converter (WEC) modeling capabilities and optimize power take-off (PTO) performance; however, these efforts have often treated WEC dynamics, PTO design, and controller development sequentially. In contrast, control co-design (CCD) is emerging as a promising strategy to address these issues directly, creating a growing need for fast analysis tools suitable for repeated simulation and parametric studies [1]. To support this need, this work presents the Multibody for Everybody (M4E) [2] linearization module, which employs a symbolic toolbox to provide deeper insight of WEC design parameters. The objective is to demonstrate that a minimal-coordinate linearization of articulated WEC dynamics can provide accurate wave response predictions and substantial computational savings relative to nonlinear time-domain simulation, while preserving compatibility with broader wave-energy analysis workflows, enabling CCD. 1.2 Approach/Activities: The proposed approach linearizes the equations of motion, generated by M4E, in minimal coordinates about a selected operating point and combines the resulting system with frequencydomain hydrodynamic terms to incorporate the reduced mass, damping, stiffness, and forcing operators. The linearized model is used for both impedance-based response amplitude operator (RAO) prediction and rapid regular-wave time integration. The methodology is demonstrated on a single-flap device and a FOSWEC configuration, with linearized M4E responses compared against the corresponding nonlinear M4E simulations and WEC-Sim results. Regular-wave time histories, RAO trends, and runtime differences are assessed. The framework is also compatible with broader wave-energy workflows, including coupling to WecOptTool, although that capability is not the focus of this work [3]. 1.3 Results/Lessons: The linearized M4E model reproduces key regularwave response characteristics such as integration and Response Amplitude over multiple frequencies. This module matches nonlinear M4E and WEC-Sim results while substantially reducing integration cost. Thus, the proposed framework can serve as a rapid analysis layer for articulated WEC design, parameter studies, and controls-oriented workflows. The analysis is most appropriate in the near-equilibrium regime, about the linearization point.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

DUNE atmospheric neutrinos: Earth tomography

In this paper we show that the DUNE experiment can measure the Earth’s density profile by analyzing atmospheric neutrino oscillations. The crucial feature that enables such measurement is the detailed event reconstruction capability of liquid argon time projection chambers. This allows for studying the sub-GeV atmospheric neutrino component, which bears a rich oscillation phenomenology, strongly dependent on the matter potential sourced by the Earth. We provide a pedagogical discussion of the MSW and parametric resonances and their role in measuring the core and mantle densities. By performing a detailed simulation, accounting for particle reconstruction at DUNE, nuclear physics effects relevant to neutrino-argon interactions and several uncertainties on the atmospheric neutrino flux, we manage to obtain a robust estimate of DUNE’s sensitivity to the Earth matter profile. We find that DUNE can measure the total mass of the Earth at 9.3% precision with an exposure of 400 kton-year. By accounting for previous measurements of the total mass and moment of inertia of the Earth, the core, lower mantle and upper mantle densities can be determined with 9%, 14% and 22% precision, respectively, for the same exposure. Finally, for a low exposure run of 60 kton-year, which would correspond to two far detectors running for three years, we have found that the core density could be measured by DUNE at ∼ 30% precision.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗
DOE OSTI2020

Final Technical Report for the SciDAC Center for the Study of Plasma Microturbulence

This final technical report for the SciDAC Center for the Study of Plasma Microturbulence documents contributions from MIT to the project over the period of the award (February 15, 2011 to February 14, 2020). This project focused on the development of neoclassical and gyrokinetic simulation capabilities relevant for the description of particle, momentum and energy transport in tokamak fusion plasmas. Extensive validation against experimental results from Alcator C-Mod and DIII-D experiments was performed. Overall areas of emphasis included gyrokinetic simulations, experiments, and observation of density gradient driven Trapped Electron Mode (TEM) turbulence relevant to burning plasmas; theory and gyrokinetic simulations of the parametric variation of the nonlinear upshift of the TEM critical density gradient; identification of a new mechanism for the isotope effect due to density gradient driven TEM turbulence; new synthetic diagnostics based on full-wave simulations which enabled unprecedented agreement between gyrokinetic simulations and measured fluctuation spectra with and without strong electron heating; development of new continuum pedestal neoclassical and turbulence codes; formulation and implementation of the first gyrokinetic exact Fokker-Planck collision operator in gyrokinetic turbulence simulations; development of new spectral approaches in velocity space for highly efficient treatments of collisions; new model collision operators implemented in the discontinuous Galerkin gyrokinetic edge turbulence code GKEYLL; and a new model and spectral code to study the interaction of ion- and electron-scale turbulence, which will serve as an efficient test-bed for multi-rate and multi-scale methods. These fundamental advances contribute to the development of a validated, predictive capability for turbulent and collisional particle, momentum and energy transport in both the core and edge of magnetically confined fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A parametric analysis of oilfield design factors affecting the detectability and characterization of electrically conductive hydrofracks

Electrical responses in the vicinity of energized steel-cased well sources offer significant potential for monitoring induced fractures. However, the high complexity of well-fracture-host models spanning multiple length scales compels analysts to simplify their numerical models due to enormous computational costs. This consequently limits our understanding regarding monitoring capabilities and the limitations of electrical measurements on realistic hydraulically fracturing systems. In this paper, we use the hierarchical finite element approach to construct geoelectric models in which geometrically complex fractures and steel-cased wells are discretely represented in 3D conducting media without sacrificing the model realism and computation efficiency. We have discovered systematic numerical analyses of the electrical responses to evaluate the influences of borehole material conductivity and the source type as well as the effects of well geometry, conductivity contrast, source location, fracture growth, and fracture propagation. Furthermore, the numerical results indicate that the borehole material property has a strong control on the electrical potentials along the production and monitoring wells. The monopole source located at a steel-cased well results in a current density distribution that decays away from the source location throughout the well length, whereas the dipole source produces a current density that dominates mainly along the dipole length. Moreover, the conductivity contrast between the fractures and host does not change the overall pattern of the electrical potentials but varies its amplitude. The fracture models near different well systems indicate that the well geometry controls the entire distribution of potentials, while the characteristics of the voltage difference profiles along the wells before and after fracturing are insensitive to the well geometry and the well in which the source is located. Further, the hydraulic-fracturing models indicate that the voltage differences along the production well before and after fracturing have strong sensitivity to fracture growth and fracture set propagation.

58 GEOSCIENCES↗
DOE OSTI2021

Thermodynamic Analysis of Thermo-vacuum Clothes Drying Operation

Clothes drying accounts for a significant amount of energy consumed in residential and commercial sectors. A thermal vacuum clothes drying technology (TVCD) is proposed as an advanced clothes dryer which can significantly reduce the energy requirements by expediting the drying process. In the conventional convective clothes dryer, hot dry air is introduced into the drum which gets in direct contact to dry the clothes. This process is energy inefficient since the significant amount of heat and the water carried out with the exhaust stream are wasted. In contrast to the conventional convective drying technique, the drying mechanism of TVCD is through nucleate boiling at low temperature due to reduced vessel pressure. The process is not only efficient but also reduces the required time for drying. The objective of this paper is to develop a comprehensive thermodynamic model to predict the transient drying process of TVCD. The three-stage system model including the detail analysis of individual components is capable of simulating the variation of the water content in the textile under various operational conditions. The preliminary results show that the drying time of 3 lb textile from 70% to 2.5% in TVCD is approximately four times less than the time required in the conventional clothes dryer. Parametric studies are carried out to understand the effect of operation conditions and component geometry on the system performance. Energy consumption of the system is also analyzed.

Yang, Cheng-Min↗