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At least 1,513 records · Page 84

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DOE OSTI2013

A portable hydro-thermo-mechanical loading cell for in-situ small angle neutron scattering studies of proton exchange membranes

A portable hydro-thermo-mechanical loading cell has been designed to enable in-situ small angle neutron scattering (SANS) studies of proton exchange membranes (PEM) under immersed tensile loadings at different temperatures. The cell consists of three main parts as follows: a letter-paper-size motor-driven mechanical load frame, a SANS friendly reservoir that provides stable immersed and thermal sample conditions, and a data acquisition & control system. The ex-situ tensile tests of Nafion 212 membranes demonstrated a satisfactory thermo-mechanical testing performance of the cell for either dry or immersed conditions at elevated temperatures. The in-situ SANS tensile measurements on the Nafion 212 membranes immersed in D2O at 70oC proved the feasibility and capability of the cell for small angle scattering study on deformation behaviors of PEM and other polymer materials under hydro-thermo-mechanical loading.

hydro-thermo-mechanical.↗

DOE OSTI2014

Load responsive multilayer insulation performance testing

Cryogenic insulation designed to operate at various pressures from one atmosphere to vacuum, with high thermal performance and light weight, is needed for cryogenically fueled space launch vehicles and aircraft. Multilayer insulation (MLI) performs well in a high vacuum, but the required vacuum shell for use in the atmosphere is heavy. Spray-on foam insulation (SOFI) is often used in these systems because of its light weight, but can have a higher heat flux than desired. We report on the continued development of Load Responsive Multilayer Insulation (LRMLI), an advanced thermal insulation system that uses dynamic beam discrete spacers that provide high thermal performance both in atmosphere and vacuum. LRMLI consists of layers of thermal radiation barriers separated and supported by micromolded polymer spacers. The spacers have low thermal conductance, and self-support a thin, lightweight vacuum shell that provides internal high vacuum in the insulation. The dynamic load responsive spacers compress to support the external load of a vacuum shell in one atmosphere, and decompress under reduced atmospheric pressure for lower heat leak. Structural load testing was performed on the spacers with various configurations. LRMLI was installed on a 400 liter tank and boil off testing with liquid nitrogen performed at various chamber pressures from one atmosphere to high vacuum. Testing was also performed with an MLI blanket on the outside of the LRMLI.

42 ENGINEERING↗

DOE OSTI2015

Mechanical properties of stanene under uniaxial and biaxial loading: A molecular dynamics study

Stanene, a graphene like two dimensional honeycomb structure of tin has attractive features in electronics application. In this study, we performed molecular dynamics simulations using modified embedded atom method potential to investigate mechanical properties of stanene. We studied the effect of temperature and strain rate on mechanical properties of α-stanene for both uniaxial and biaxial loading conditions. Our study suggests that with the increasing temperature, both the fracture strength and strain of the stanene decrease. Uniaxial loading in zigzag direction shows higher fracture strength and strain compared to the armchair direction, while no noticeable variation in the mechanical properties is observed for biaxial loading. We also found at a higher loading rate, material exhibits higher fracture strength and strain. These results will aid further investigation of stanene as a potential nano-electronics substitute.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Cavitation erosion prediction based on analysis of flow dynamics and impact load spectra

Cavitation erosion is the consequence of repeated collapse-induced high pressure-loads on a material surface. The present paper assesses the prediction of impact load spectra of cavitating flows, i.e., the rate and intensity distribution of collapse events based on a detailed analysis of flow dynamics. Data are obtained from a numerical simulation which employs a density-based finite volume method, taking into account the compressibility of both phases, and resolves collapse-induced pressure waves. To determine the spectrum of collapse events in the fluid domain, we detect and quantify the collapse of isolated vapor structures. As reference configuration we consider the expansion of a liquid into a radially divergent gap which exhibits unsteady sheet and cloud cavitation. Analysis of simulation data shows that global cavitation dynamics and dominant flow events are well resolved, even though the spatial resolution is too coarse to resolve individual vapor bubbles. The inviscid flow model recovers increasingly fine-scale vapor structures and collapses with increasing resolution. We demonstrate that frequency and intensity of these collapse events scale with grid resolution. Scaling laws based on two reference lengths are introduced for this purpose. We show that upon applying these laws impact load spectra recorded on experimental and numerical pressure sensors agree with each other. Furthermore, correlation between experimental pitting rates and collapse-event rates is found. Locations of high maximum wall pressures and high densities of collapse events near walls obtained numerically agree well with areas of erosion damage in the experiment. The investigation shows that impact load spectra of cavitating flows can be inferred from flow data that captures the main vapor structures and wave dynamics without the need for resolving all flow scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Mechanical response of lithium fluoride under off-principal dynamic shock-ramp loading

Single crystal lithium fluoride (LiF), oriented [100], was shock loaded and subsequently shocklessly compressed in two experiments at the Z Machine. We employed velocimetry measurements in order to obtain an impactor velocity, shock transit times, and in-situ particle velocities for LiF samples up to ~1.8 mm thick. We also performed a dual thickness Lagrangian analysis on the in-situ velocimetry data to obtain the mechanical response along the loading path of these experiments. Finally, we observed an elastic response on one experiment during initial shockless compression from 100 GPa before yielding. The relatively large thickness differences utilized for the dual sample analyses (up to ~1.8 mm) combined with a relative timing accuracy of ~0.2 ns resulted in an uncertainty of less than 1% on density and stress at ~200 GPa peak loading on one experiment and <4% on peak loading at ~330 GPa for another. The stress-density analyses from these experiments compare favorably with recent equation of state models for LiF.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Detection of an anomalous pressure on a magneto-inertial-fusion load current diagnostic

Recent Magnetized Liner Inertial Fusion experiments at the Sandia National Laboratories Z pulsed power facility have featured a PDV (Photonic Doppler Velocimetry) diagnostic in the final power feed section for measuring load current. In this paper, we report on an anomalous pressure that is detected on this PDV diagnostic very early in time during the current ramp. Early time load currents that are greater than both B-dot upstream current measurements and existing Z machine circuit models by at least 1 MA would be necessary to describe the measured early time velocity of the PDV flyer. This leads us to infer that the pressure producing the early time PDV flyer motion cannot be attributed to the magnetic pressure of the load current but rather to an anomalous pressure. Using the MHD code ALEGRA, we are able to compute a time-dependent anomalous pressure function, which when added to the magnetic pressure of the load current, yields simulated flyer velocities that are in excellent agreement with the PDV measurement. As a result, we also provide plausible explanations for what could be the origin of the anomalous pressure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Measurement of toroidal variation in conducted heat loads in locked mode induced disruptions on DIII-D

Locked mode disruptions with controlled toroidal phase are produced in the DIII-D tokamak by locking to large non-axisymmetric applied magnetic perturbations with different toroidal phases. Additionally, the disruption conducted heat loads are found to go almost completely to the outer divertor region, possibly due to strong inner leg detachment, but possibly also due to plasma motion and limiting on the outer divertor leg shelf. The outer leg conducted heat loads are found to have a significant toroidal variation of order ±30%, with a dominantly n = 1 structure. The heat load phase is shifted from initial locked mode phase in a way that is approximately consistent with heat loss into the scrape-off layer being enhanced at the mode island O-point outer midplane crossing. These measurements suggest that pre-existing locked modes can affect the conducted heat load structure during the thermal quench by affecting the thermal quench MHD phase. This is consistent with previous MHD simulations which indicated that pre-disruption locked mode structures can persist and survive to some degree through the large thermal quench MHD. Finally, this work complements previous work [Shiraki2015] which showed that n = 1 structures in mitigated disruptions can create toroidal variation in the disruption radiated power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Ablation loading of barium ions into a surface-electrode trap

Trapped-ion quantum information processing may benefit from qubits encoded in isotopes that are practically available in only small quantities, e.g., due to low natural abundance or radioactivity. Laser ablation provides a method of controllably liberating neutral atoms or ions from low-volume targets, but energetic ablation products can be difficult to confine in the small ion-electrode distance, micron-scale microfabricated traps amenable to high-speed, high-fidelity manipulation of ion arrays. Here, we investigate ablation-based ion loading into surface-electrode traps of different sizes to test a model describing ion loading probability as a function of effective trap volume and other trap parameters. We characterize loading of ablated barium from a metallic source in two cryogenic surface-electrode traps with 730 and 50 μm ion-electrode distances. Furthermore, our loading rate agrees with a predictive analytical model, providing insight for the confinement of limited-quantity species of interest for quantum computing, simulation, and sensing.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Thermal Energy Storage Configurations for Small Modular Reactor Load Shedding

The increased penetration of intermittent renewable energy technologies such as wind and solar power can strain electric grids, forcing carbon-based and nuclear sources of energy to operate in a load follow mode. For nuclear reactors, load follow operation can be undesirable due to the associated thermal and mechanical stresses placed on the fuel and other reactor components. Various methods of Thermal Energy Storage (TES) can be coupled to nuclear (or renewable) power sources to help absorb grid variability caused by daily load demand changes and renewable intermittency. Two TES techniques are investigated as candidate thermal reservoirs to be used in conjunction with a Small Modular Reactor (SMR): a two-tank sensible heat storage system and a stratified chilled-water storage system. The goal when coupling the two systems to the SMR is to match turbine output and demand and bypass steam to the TES systems to maintain reactor power at approximately 100%. Simulations of IPWR dynamics are run in a high-fidelity FORTRAN model developed at NCSU. Both TES systems are developed as callable FORTRAN subroutines to model the time-varying behavior associated with different configurations of these systems when connected to the SMR simulator. Simulation results reveal the sensible heat storage system is capable of meeting turbine demand and maintaining reactor power constant, while providing enough steam to power four absorption chillers for chilled-water production and storage. Here,the stored chilled water is used to supplement cooling loads of an adjacent facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Loading Capacity and Dilute Nitric Acid Rinse of Diglycolamide Resin for the Recovery of Transplutonium and Rare Earth Elements from Mark-18A Targets

N,N,N′,N′-tetraoctyldiglycolamide (TODGA) as a resin (“DGA resin”) produced by Eichrom Technologies will be used by Savannah River National Laboratory for the indiscriminate extraction of trivalent actinides and rare earth elements with the intent of recovering Cm and Am from dissolved irradiated 242 Pu Mark-18A targets in 7 to 9 M nitric acid. The extracted constituents will be recovered as an oxide by direct thermal decomposition of the loaded resin followed by calcination of the resultant residue. The characteristics of DGA resin with non-radiological feed simulant representative of the anticipated feed in the Mark-18A process, with Sm and Nd as surrogates for Cm and Am, respectively, including breakthrough point and saturation capacity were evaluated in this work. Additionally, this work examined the losses from the loaded resin by rinsing the resin bed with dilute acid to reduce the nitrate concentration in the resin bed prior to thermal decomposition operations to improve the safety posture of the process. A resin loading profile was developed, and the resin was determined to have a trivalent metal saturation capacity of 74 μmol/mL resin under the experimental conditions evaluated. Following a wash of the loaded resin bed with fresh 8 M HNO 3 , the trivalent metals retained was reduced to 68 μmol/mL resin, which represents the practical capacity of the resin for the Mark-18A process. Lighter lanthanides breakthrough the resin well before the saturation capacity is reached. Rinsing the saturated resin bed with 0.26 M HNO 3 was found to result in a rapid reduction in retention of rare earth elements by the resin. After 2.8 bed volumes of dilute acid rinse, the mean resin bed free acid concentration was reduced to 0.28 M and 3.1 bed volumes of dilute acid rinse resulted in a reduction of the cumulative rare earth element retention to 52 μmol/mL of resin.

Transplutonium separations↗

DOE OSTI2013

HYPERACCRETING BLACK HOLE AS GAMMA-RAY BURST CENTRAL ENGINE. I. BARYON LOADING IN GAMMA-RAY BURST JETS

A hyperaccreting stellar-mass black hole has been long speculated as the best candidate for the central engine of gamma-ray bursts (GRBs). Recent rich observations of GRBs by space missions such as Swift and Fermi pose new constraints on GRB central engine models. In this paper, we study the baryon-loading processes of a GRB jet launched from a black hole central engine. We consider a relativistic jet powered by {nu} {nu}-bar -annihilation or by the Blandford-Znajek (BZ) mechanism. We consider baryon loading from a neutrino-driven wind launched from a neutrino-cooling-dominated accretion flow. For a magnetically dominated BZ jet, we consider neutron drifting from the magnetic wall surrounding the jet and subsequent positron capture and proton-neutron inelastic collisions. The minimum baryon loads in both types of jet are calculated. We find that in both cases a more luminous jet tends to be more baryon poor. A neutrino-driven ''fireball'' is typically ''dirtier'' than a magnetically dominated jet, while a magnetically dominated jet can be much cleaner. Both models have the right scaling to interpret the empirical {Gamma}-L{sub iso} relation discovered recently. Since some neutrino-driven jets have too much baryon loading as compared with the data, we suggest that at least a good fraction of GRBs should have a magnetically dominated central engine.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Effects of cathode loadings and anode protection on the performance of lithium metal batteries

Abstract While lithium-ion batteries (LIBs) are approaching their energy limits, lithium metal batteries (LMBs) are undergoing intensive investigation for higher energy density. Coupling LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathode with lithium (Li) metal anode, the resultant Li||NMC811 LMBs are among the most promising technologies for future transportation electrification, which have the potential to realize an energy density two times higher than that of state-of-the-art LIBs. To maximize their energy density, the Li||NMC811 LMBs are preferred to have their cathode loading as high as possible while their Li anode as thin as possible. To this end, we investigated the effects of different cathode active material loadings (2–14 mg cm −2 ) on the performance of the Li||NMC811 LMBs. Our study revealed that the cathode loadings have remarkably affected the cell performance, in terms of capacity retention and sustainable capacity. Cells with high cathode loadings are more liable to fade in capacity, due to more severe formation of the CEI and more sluggish ion transport. In this study, we also verified that the protection of the Li anode is significant for achieving better cell performance. In this regard, our newly developed Li-containing glycerol (LiGL) via molecular layer deposition (MLD) is promising to help boost the cell performance, which was controllably deposited on the Li anode.

Materials Science↗

DOE OSTI2021

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs

Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.

Thavappiragasam, Mathialakan↗

DOE OSTI2020

A Privacy Preserving Model-Free Optimization and Control Framework for Demand Response from Residential Thermal Loads

We consider the problem of optimizing the cost of procuring electricity for a large collection of homes managed by a load serving entity, by pre-cooling or pre-heating the thermal inertial loads in the homes to avoid procuring power during periods of peak electricity pricing. We would like to accomplish this objective in a completely privacy-preserving and model-free manner, that is, without direct access to the state variables (temperatures or power consumption) or the dynamical models (thermal characteristics) of individual homes, while guaranteeing personal comfort constraints of the consumers. We propose a two-stage optimization and control framework to address this problem. In the first stage, we use a long short-term memory (LSTM) network to predict hourly electricity prices, based on historical pricing data and weather forecasts. Given the hourly price forecast and thermal models of the homes, the problem of designing an optimal power consumption trajectory that minimizes the total electricity procurement cost for the collection of thermal loads can be formulated as a large-scale integer program (with millions of variables) due to the on-off cyclical dynamics of such loads. We provide a simple heuristic relaxation to make this large-scale optimization problem model-free and computationally tractable. In the second stage, we translate the results of this optimization problem into distributed open-loop control laws that can be implemented at individual homes without measuring or estimating their state variables, while simultaneously ensuring consumer comfort constraints. We demonstrate the performance of this approach on a large-scale test case comprising of 500 homes in the Houston area and benchmark its performance against a direct model-based optimization and control solution.

Sivaranjani, S.↗

DOE OSTI2018

Privacy-Preserving Aggregation of Controllable Loads to Compensate Fluctuations in Solar Power

Cybersecurity and privacy are of the utmost importance for safe, reliable operation of the electric grid. It is well known that the increased connectivity/interoperability between all stakeholders (e.g., utilities, suppliers, and consumers) will enable personal information collection. Significant advanced metering infrastructure (AMI) deployment and demand response (DR) programs across the country, while enable enhanced automation, also generate energy data on individual consumers that can potentially be used for exploiting privacy. Inspired by existing works which consider DR, battery-based perturbation, and differential privacy noise adding, we novelly consider the aggregator (cluster) level privacy issue in the DR framework of solar photovoltaic (PV) generation following. Different from most of the existing works which mainly rely on the charging/discharging scheduling of rechargeable batteries, we utilize controllable building loads to serve as virtual storage devices to absorb a large portion of the PV genertaion while delicately keeping desired noisy terms to satisfy the differential privacy for the raw load profiles at the aggregator level. This not only ensures differential privacy, but also improves the DR efficiency in load following since part of the noisy signal in solar PV generation has been filtered out. In particular, a mixed integer quadratic optimization problem is formulated to optimally dispatch a population of on/off controllable loads to achieve this privacy-preserving DR service.

Dong, Jin↗

DOE OSTI2020

Frequency-domain Flexibility Characterization of Heterogeneous End-use Loads for Grid Services

Demand response, based on flexible loads, has been a novel and important proposal for smart grids. A population of small loads can be aggregated to provide ancillary services to the grid and generate value for the owners. In this paper, we investigate the flexibility of such populations from the frequency-domain perspective. We propose a methodology to characterize the frequency-dependent flexibility of heterogeneous populations of loads considering practical constraints. The resultant frequency-domain characterization can help flexible load aggregators assess the capability of contracted populations. System operators can also benefit from a better understanding of the capabilities of the service providers. The effectiveness of the methodology is demonstrated by simulations.

Wang, Dexin↗

DOE OSTI2024

Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net-Load Forecasting

Accurate net-load forecasting is vital for energy planning, aiding decisions on trade and load distribution. However, assessing the performance of forecasting models across diverse input variables, like temperature and humidity, remains challenging, particularly for eliciting a high degree of trust in the model outcomes. In this context, there is a growing need for data-driven technological interventions to aid scientists in comprehending how models react to both noisy and clean input variables, thus shedding light on complex behaviors and fostering confidence in the outcomes. In this paper, we present Forte, a visual analytics-based application to explore deep probabilistic net-load forecasting models across various input variables and understand the error rates for different scenarios. With carefully designed visual interventions, this web-based interface empowers scientists to derive insights about model performance by simulating diverse scenarios, facilitating an informed decision-making process. We discuss observations made using Forte and demonstrate the effectiveness of visualization techniques to provide valuable insights into the correlation between weather inputs and net-load forecasts, ultimately advancing grid capabilities by improving trust in forecasting models.

Bhattacharjee, Kaustav↗

DOE OSTI2024

Weather Sensitive High Spatio-Temporal Resolution Transportation Electric Load Profiles For Multiple Decarbonization Pathways

Electrification of transport compounded with climate change will transform hourly load profiles and their response to weather. We present a novel approach to generating hourly electric load profiles that considers charging strategies and evolving sensitivity to temperature. The approach consists of downscaling annual state-scale sectoral load projections from the multisectoral Global Change Analysis Model (GCAM) into hourly electric load profiles leveraging high resolution climate and population datasets. Profiles are developed and evaluated at the Balancing Authority scale, with a 5-year increment until 2050 over the Western U.S. Interconnect for multiple decarbonization pathways and climate scenarios. The datasets are readily available for production cost model analysis. Our open source approach is transferable to other regions.

Decarbonization, tranportation, Electric vehicle c↗