Search NASA⌕ Search

SEARCH · Search NASA

Results for “system sizing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

Toward scalable quantum computations of atomic nuclei

We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitary coupled cluster theory to parametrize the ground states of the deuteron and 3 He, compute their corresponding energies, and analyze the scaling of the required computational resources. Our quantum simulations reproduce exact benchmarks for 2 H and 3 He within 100 keV, requiring at most 30 layers in the ansatz and thus resulting in modest circuit depths. Additionally, we find the number of shots required to reach a given precision scales linearly in the lattice size and more mildly in the system size. Furthermore, based on the agreement with exact benchmarks and mild scaling, we conclude that this can be an efficient, scalable approach for quantum computations of nuclear ground states, particularly to prepare initial states for quantum phase estimation or other filtering algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. Here, we introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

Thomas, Phillip S. [Lawrence Berkeley National Lab↗

Theory of Trotter Error with Commutator Scaling

The Lie-Trotter formula, together with its higher-order generalizations, provides a simple approach to decomposing the exponential of a sum of operators. Despite significant effort, the error scaling of such product formulas remains poorly understood. We develop a theory of Trotter error that overcomes the limitations of truncating the Baker-Campbell-Hausdorff expansion. Our analysis directly exploits the commutativity of operator summands, producing tighter error bounds for both real- and imaginary-time evolutions. Whereas previous work achieves similar goals for systems with geometric locality or Lie-algebraic structure, our approach holds in general. We give a host of improved algorithms for digital quantum simulation and quantum Monte Carlo methods, nearly matching or even outperforming the best previous results. Our applications include: (i) a simulation of second-quantized plane-wave electronic structure, nearly matching the interaction-picture algorithm of Low and Wiebe; (ii) a simulation of $k$-local Hamiltonians almost with induced one-norm scaling, faster than the qubitization algorithm of Low and Chuang; (iii) a simulation of rapidly decaying power-law interactions, outperforming the Lieb-Robinson-based approach of Tran et al.; (iv) a hybrid simulation of clustered Hamiltonians, dramatically improving the result of Peng, Harrow, Ozols, and Wu; and (v) quantum Monte Carlo simulations of the transverse field Ising model and quantum ferromagnets, tightening previous analyses of Bravyi and Gosset. We obtain further speedups using the fact that product formulas can preserve the locality of the simulated system. Specifically, we show that local observables can be simulated with complexity independent of the system size for power-law interacting systems, which implies a Lieb-Robinson bound nearly matching a recent result of Tran et al. Our analysis reproduces known tight bounds for first- and second-order formulas. We further investigate the tightness of our bounds for higher-order formulas. For quantum simulation of a one-dimensional Heisenberg model with an even-odd ordering of terms, our result overestimates the complexity by only a factor of $5$. Our bound is also close to tight for power-law interactions and other orderings of terms. This suggests that our theory can accurately characterize Trotter error in terms of both the asymptotic scaling and the constant prefactor.

quantum computing, numerical analysis↗

Terrestrial applications of FEP-encapsulated solar cell modules

FEP-encapsulated solar cell modules and arrays have been designed and built expressly for terrestrial applications. System design including solar cell array mechanical design and the approach to system sizing is outlined. Such solar cell systems have been installed at six sites. Individual modules have undergone marine environment tests. Results from seven months of operation indicate that system is meeting its electrical design requirements. No mechanical degradation has been reported. The array on Mammoth Mountain, California has been damaged by rime ice but shows no loss in electrical output. Marine environment tests on single modules have shown that elements of the module must be completely sealed by the FEP. Based on the limited test data available, the FEP-encapsulated solar cell module appears well suited to terrestrial applications.

Forestieri, A. F.↗

Terrestrial applications of FEP-encapsulated solar cell modules

FEP-encapsulated solar cell modules and arrays have been designed and built expressly for terrestrial applications. System design including solar cell array mechanical design and the approach to system sizing is outlined. Such solar cell systems have been installed at six sites. Individual modules have undergone marine environment tests. Results from seven months of operation indicate that the system is meeting its electrical design requirements. No mechanical degradation has been reported. An array on Mammoth Mountain, California has been damaged by rime ice but shows no loss in electrical output. Marine environment tests on single modules have shown that elements of the module must be completely sealed by the FEP. Based on the limited test data available, the FEP-encapsulated solar cell module appears well suited to terrestrial applications.

Forestieri, A. F.↗

Error estimation for ORION baseline vector determination

Effects of error sources on Operational Radio Interferometry Observing Network (ORION) baseline vector determination are studied. Partial derivatives of delay observations with respect to each error source are formulated. Covariance analysis is performed to estimate the contribution of each error source to baseline vector error. System design parameters such as antenna sizes, system temperatures and provision for dual frequency operation are discussed.

Wu, S. C.↗

The Effect of Altitude Conditions on the Particle Emissions of a J85-GE-5L Turbojet Engine

Particles from a J85-GE-5L turbojet engine were measured over a range of engine speeds at simulated altitude conditions ranging from near sea level to 45,000 ft and at flight Mach numbers of 0.5 and 0.8. Samples were collected from the engine by using a specially designed probe positioned several inches behind the exhaust nozzle. A differential mobility particle sizing system was used to determine particle size. Particle data measured at near sea-level conditions were compared with Navy Aircraft Environmental Support Office (AESO) particle data taken from a GE-J85-4A engine at a sea-level static condition. Particle data from the J85 engine were also compared with particle data from a J85 combustor at three different simulated altitudes.

Rickey, June Elizabeth↗

Nuclear Interdiction Through Relocatable Detectors

The NNSA Office of Nuclear Smuggling Detection and Deterrence (NSDD) has investigated a set of minimal-infrastructure radiation detection systems as alternatives to fixed Radiation Portal Monitors (RPMs) for nuclear interdiction applications. These versatile and relocatable systems can improve nuclear security in missions or locations that do not warrant or support a standard fixed radiation detection system. Over 2019, a variety of relocatable detectors were characterized at the Interdiction Technologies Integration Laboratory at Pacific Northwest National Laboratory (PNNL). Evaluated detectors were diverse in their size and capabilities, ranging from backpack-sized systems to lane-spanning cargo scanning portals. Both spectroscopic and non-spectroscopic pedestrian and vehicle detection systems were characterized against uranium and plutonium sources. Signatures from the sources were modulated by both shielding and distance to quantify the performance of the relocatable systems as signal strength was decreased. Findings showed that relocatable spectroscopic detectors with isotope identification capabilities could reduce nuisance alarm rates compared to conventional fixed installation, gross-counting, radiation portal monitors. In vehicle scanning applications, detection ability generally trended with detection volume, regardless of spectral capability. In pedestrian scanning applications, several smaller backpack-sized detector systems were found to be more sensitive to detecting material than pedestrian portal monitors. The results of this characterization effort have helped inform the deployment of versatile equipment to improve nuclear security missions.

relocatable detectors, Nuclear Security↗

Modeling a Transient Pressurization with Active Cooling Sizing Tool

As interest in the area of in-space zero boil-off cryogenic propellant storage develops, the need to visualize and quantify cryogen behavior during ventless tank self-pressurization and subsequent cool-down with active thermal control has become apparent. During the course of a mission, such as the launch ascent phase, there are periods that power to the active cooling system will be unavailable. In addition, because it is not feasible to install vacuum jackets on large propellant tanks, as is typically done for in-space cryogenic applications for science payloads, instances like the launch ascent heating phase are important to study. Numerous efforts have been made to characterize cryogenic tank pressurization during ventless cryogen storage without active cooling, but few tools exist to model this behavior in a user-friendly environment for general use, and none exist that quantify the marginal active cooling system size needed for power down periods to manage tank pressure response once active cooling is resumed. This paper describes the Transient pressurization with Active Cooling Tool (TACT), which is based on a ventless three-lump homogeneous thermodynamic self-pressurization model1 coupled with an active cooling system estimator. TACT has been designed to estimate the pressurization of a heated but unvented cryogenic tank, assuming an unavailable power period followed by a given cryocooler heat removal rate. By receiving input data on the tank material and geometry, propellant initial conditions, and passive and transient heating rates, a pressurization and recovery profile can be found, which establishes the time needed to return to a designated pressure. This provides the ability to understand the effect that launch ascent and unpowered mission segments have on the size of an active cooling system. A sample of the trends found show that an active cooling system sized for twice the steady state heating rate would results in a reasonable time for tank pressure recovery with ZBO of a liquid oxygen propellant tank.

Guzik, Monica C.↗

Assessing uncertainty in the timing of energy use during cost-optimal distributed energy technology selection and sizing

This paper empirically derives uncertainty ranges in cost-optimal solar PV and storage sizing by comparing results from the REopt Lite optimization platform from metered data and a set of simulated Department of Energy Commercial Reference Building (CRB) profiles at 65 sites. We find load profile shape alone does not explain a site’s optimal configurations (i.e., PV, Storage, PV and Storage, No System). Still, load profile shape does introduce uncertainty to optimal PV and storage capacities. Across all cases where PV is part of an optimal configuration, we find the average ratio of power capacities derived from metered loads to capacities derived from CRB profiles to be 0.97 (and as high as 1463), where 1 would be a perfect match in system size. For storage, the ratio is 1.6 (and as high as 42). We also assess how, in the absence of complete metered data, a CRB profile can be selected that would be expected to yield the most similar solar PV and storage capacities. From those metrics that can be available from billing data (i.e., peak demand, monthly load totals), we find that uncertainty is most reduced by selecting the CRB’s with an annual peak occurring at the most similar time, or those with the lowest average root mean square error (RMSE) among monthly peak loads. This research can help improve the implementation and interpretation of results derived from simulated load profiles and is an important next step in advancing smart grid solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Glassy Word Problems: Ultraslow Relaxation, Hilbert Space Jamming, and Computational Complexity

We introduce a family of local models of dynamics based on “word problems” from computer science and group theory, for which we can place rigorous lower bounds on relaxation timescales. These models can be regarded either as random circuit or local Hamiltonian dynamics and include many familiar examples of constrained dynamics as special cases. The configuration space of these models splits into dynamically disconnected sectors, and for initial states to relax, they must “work out” the other states in the sector to which they belong. When this problem has a high time complexity, relaxation is slow. In some of the cases we study, this problem also has high space complexity. When the space complexity is larger than the system size, an unconventional type of jamming transition can occur, whereby a system of a fixed size is not ergodic but can be made ergodic by appending a large reservoir of sites in a trivial product state. This finding manifests itself in a new type of Hilbert space fragmentation that we call fragile fragmentation. We present explicit examples where slow relaxation and jamming strongly modify the hydrodynamics of conserved densities. In one example, density modulations of wave vector q exhibit almost no relaxation until times O ( exp ( 1 / q ) ) , at which point they abruptly collapse. We also comment on extensions of our results to higher dimensions. Published by the American Physical Society 2024

Physics↗

Deviations from maximal entanglement for eigenstates of the Sachdev-Ye-Kitaev model

We consider mid-spectrum eigenstates of the Sachdev-Ye-Kiteav (SYK) model. We prove that for subsystems whose size is a constant fraction of the system size, the entanglement entropy deviates from the maximum entropy by at least a positive constant. This result highlights the difference between the entanglement entropy of mid-spectrum eigenstates of the SYK model and that of random states.

Disordered Systems and Neural Networks (cond-mat.d↗

Optimizing design and dispatch of a renewable energy system

Renewable energy technologies are becoming increasingly important due to their cost-competitiveness, and because of enhanced climate concerns. We demonstrate the capabilities of an integer-programming optimization model that minimizes capital (investment) and operational costs, and utility charges, while adhering to system sizing constraints, demand requirements, and interoperability characteristics of the systems chosen. Furthermore, the model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies, while simultaneously optimizing the corresponding dispatch strategy. Our case studies explore several venues, i.e., a small campus and a local hospital, with complex utility rate tariffs, multi-technology integration opportunities, and incentives for renewable power production. Using an optimization model, versus applying rules of thumb, can produce millions of dollars in savings over a 25-year time horizon and result in thousands of kilowatts of installed renewable energy.

25 ENERGY STORAGE↗

Enhanced production of strange baryons in high-energy nuclear collisions from a multiphase transport model

Here, we introduce additional coalescence factors for the production of strange baryons in a multiphase transport (AMPT) model in order to describe the enhanced production of multistrange hadrons observed in Pb + Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV at the Large Hadron Collider (LHC) and Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV at Relativistic Heavy-Ion Collider (RHIC). This extended AMPT model is found to also give a reasonable description of the multiplicity dependence of the strangeness enhancement observed in high multiplicity events in $\textit{pp}$ collisions at $\sqrt{s}$ = 7 TeV and $\textit{p}$-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV. We find that the coalescence factors depend on the system size but not much on whether the system is produced from A + A or $\textit{p}$ + A collisions. Here, the extended AMPT model thus provides a convenient way to model the mechanism underlying the observed strangeness enhancement in collisions of both small and large systems at RHIC and LHC energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

First-principles calculation of the configurational energy density of states for a solid-state ion conductor with a variant of the Wang and Landau algorithm

In this work, a variant of the Wang and Landau algorithm for calculation of the configurational energy density of states is proposed. The algorithm was developed for the purpose of using first-principles simulations, such as density functional theory, to calculate the partition function of disordered sublattices in crystal materials. The expensive calculations of first-principles methods make a parallel algorithm necessary for a practical computation of the configurational energy density of states within a supercell approximation of a solid-state material. The algorithm developed in this work is tested with the two-dimensional (2d) Ising model to bench mark the algorithm and to help provide insight for implementation to a materials science application. Tests with the 2d Ising model revealed that the algorithm has good performance compared to the original Wang and Landau algorithm and the 1/$\textit{t}$ algorithm, in particular the short iteration performance. Further, a proof of convergence is presented within an adiabatic assumption, and the analysis is able to correctly predict the time dependence of the modification factor to the density of states. The algorithm was then applied to the lithium and lanthanum sublattice of the solid-state lithium ion conductor Li 0.5 La 0.5 TiO 3 . This was done to help understand the disordered nature of the lithium and lanthanum. The results find, overall, that the algorithm performs very well for the 2d Ising model and that the results for Li 0.5 La 0.5 TiO 3 are consistent with experiment while providing additional insight into the lithium and lanthanum ordering in the material. The primary result is that the lithium and lanthanum become more mixed between layers along the c axis for increasing temperature. In part, the simulation of the disordered Li 0.5 La 0.5 TiO 3 system serves as a benchmark for what size systems are currently and in the near future practical to calculate with density functional theory methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sparse Linear Solvers for Large-scale Electromagnetic Transient Simulations

Linear solvers form the basis for electromagnetic transient (EMT) simulations. There is a need to speed up EMT simulations as larger regions are analyzed using EMT simulations. For the same, the performance of linear solvers plays an important role. Exploiting the sparsity of the matrices generated in EMT simulations could assist with speed-up. Scalability is also crucial as power grids expand, demanding solutions capable of accommodating the increasing system size. Recent studies from the North American Electric Reliability Corporation (NERC) increasingly emphasize that EMT simulation models of the power grid will grow larger with the inclusion of power electronics components. Parallelisms in sparsity patterns exploit modern central processing units (CPUs), multi-core CPUs, and graphics processing units (GPUs) architectures in sparse solver designs. Therefore, this paper explores publicly available existing linear solvers and investigates their efficiency in large-scale power grid simulations. A large-scale power grid is developed by increasing the size of the IEEE 39 bus test system to up to 39000 bus systems.

Hsu, Kuan-Chieh↗

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗

Practical aspects of photovoltaic technology, applications and cost (revised)

The purpose of this text is to provide the reader with the background, understanding, and computational tools needed to master the practical aspects of photovoltaic (PV) technology, application, and cost. The focus is on stand-alone, silicon solar cell, flat-plate systems in the range of 1 to 25 kWh/day output. Technology topics covered include operation and performance of each of the major system components (e.g., modules, array, battery, regulators, controls, and instrumentation), safety, installation, operation and maintenance, and electrical loads. Application experience and trends are presented. Indices of electrical service performance - reliability, availability, and voltage control - are discussed, and the known service performance of central station electric grid, diesel-generator, and PV stand-alone systems are compared. PV system sizing methods are reviewed and compared, and a procedure for rapid sizing is described and illustrated by the use of several sample cases. The rapid sizing procedure yields an array and battery size that corresponds to a minimum cost system for a given load requirement, insulation condition, and desired level of service performance. PV system capital cost and levelized energy cost are derived as functions of service performance and insulation. Estimates of future trends in PV system costs are made.

Rosenblum, L.↗