Predictive Models from Quantum Computer Benchmarks
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Explore the source record for details and available documents.
As worldwide use of residential photovoltaic (PV) systems grows, system operators and utilities will need to transition from forecasting pure demand to forecasting net load with behind-the-meter (BTM) PV generation. However, PV generation can be difficult to predict and the measurements of PV generation from BTM residential systems are often invisible behind a measurement of the net load, making net load forecasting challenging. This paper proposes a novel two-stage framework for net load forecasting in areas with limited observability and high BTM PV generation. First, the profiles of observable customers are used to disaggregate the net load measurements into the pure load and PV generation. Then, separate models are used to forecast the PV generation and pure load individually, and the results are combined for a net load forecast. Further, this paper also proposes a compensator for correcting the error of the net load forecast, using historical forecast errors of the PV generation, pure load, and net load. The proposed framework is tested through two case studies for areas with high BTM PV penetration and less than 10% observable customers. The two-stage forecasting model is compared to two benchmark methods - a time series forecasting model, and a model that forecasts the net load directly using historical net load measurements. Results show that the proposed disaggregation-forecasting framework reduces the error of the net load forecast compared to both benchmark models. In addition, when the net load forecast error is periodic, the compensator can correct the error to improve the forecast accuracy.
A note of errata prepended to the Godiva-IV delayed-critical benchmark (HEU-MET-FAST- 086) identifies two corrections to be made to the model: The glory hole in the spindle should be made larger, and the height of the safety block should be made smaller (and therefore its density made larger). In addition, the safety block at its full-in position is closer to the inner subassembly plate than was modeled in the benchmark. These changes have been made to HEU-MET-FAST-086 Case 4 in order to estimate the effect on $\kappa$ eff and on the neutron flux spectrum. Using smaller separation, a smaller safety block, and a larger glory hole caused keff to increase by 453 ± 1 pcm from the benchmark. The latest nuclear data, ENDF/B-VIII.0, have also been used, causing $\kappa$ eff to increase another 37 ± 1 pcm. Flux spectra were compared in a modeled fission foil (near the center of Godiva-IV in the glory hole) and at three external (point) detectors. Within the fission foil, using ENDF/B-VIII.0 induced changes in the flux spectrum similar in size to the changes due to using smaller separation, a smaller safety block, and a larger glory hole. At the detectors, using ENDF/B- VIII.0 induced changes in the flux spectrum much larger than those due to changing the model. In other words, the corrections to the benchmark model cause a large increase in $\kappa$ eff , but the changes to the neutron flux spectrum are small compared to those caused by using the latest nuclear data. This study presents a preview of results expected during the reevaluation of the Godiva IV benchmark, but it is not a substitute for the full reevaluation.A note of errata prepended to the Godiva-IV delayed-critical benchmark (HEU-MET-FAST- 086) identifies two corrections to be made to the model: The glory hole in the spindle should be made larger, and the height of the safety block should be made smaller (and therefore its density made larger). In addition, the safety block at its full-in position is closer to the inner subassembly plate than was modeled in the benchmark. These changes have been made to HEU-MET-FAST-086 Case 4 in order to estimate the effect on $\kappa$ eff and on the neutron flux spectrum. Using smaller separation, a smaller safety block, and a larger glory hole caused $\kappa$ eff to increase by 453 ± 1 pcm from the benchmark. The latest nuclear data, ENDF/B-VIII.0, have also been used, causing $\kappa$ eff to increase another 37 ± 1 pcm. Flux spectra were compared in a modeled fission foil (near the center of Godiva-IV in the glory hole) and at three external (point) detectors. Within the fission foil, using ENDF/B-VIII.0 induced changes in the flux spectrum similar in size to the changes due to using smaller separation, a smaller safety block, and a larger glory hole. At the detectors, using ENDF/B- VIII.0 induced changes in the flux spectrum much larger than those due to changing the model. In other words, the corrections to the benchmark model cause a large increase in $\kappa$ eff , but the changes to the neutron flux spectrum are small compared to those caused by using the latest nuclear data. This study presents a preview of results expected during the reevaluation of the Godiva IV benchmark, but it is not a substitute for the full reevaluation.
Abstract The persistent and growing spread in effective climate sensitivity (ECS) across global climate models necessitates rigorous evaluation of their cloud feedbacks. Here we evaluate several cloud feedback components simulated in 19 climate models against benchmark values determined via an expert synthesis of observational, theoretical, and high‐resolution modeling studies. We find that models with smallest feedback errors relative to these benchmark values generally have moderate total cloud feedbacks (0.4–0.6 W m −2 K −1 ) and ECS (3–4 K). Those with largest errors generally have total cloud feedback and ECS values that are too large or too small. Models tend to achieve large positive total cloud feedbacks by having several cloud feedback components that are systematically biased high rather than by having a single anomalously large component, and vice versa. In general, better simulation of mean‐state cloud properties leads to stronger but not necessarily better cloud feedbacks. The Python code base provided herein could be applied to developmental versions of models to assess cloud feedbacks and cloud errors and place them in the context of other models and of expert judgment in real‐time during model development.
In this work, the shape and collectivity of 80 Ge were investigated via a sub-barrier-energy Coulomb excitation measurement using the JANUS setup at the NSCL ReA3 facility. The 80 Ge spectroscopic quadrupole moment $Q_{s}(2^{+}_{1})$ of the $2^{+}_{1}$ state was measured for the first time, and the precision of the 80 Ge $B(E2; 0^{+}_{1}$ → $2^{+}_{1}$) transition strength was increased. The experimental $Q_{s}(2^{+}_{1})$ value indicates a large, prolate deformation for 80 Ge, which is consistent with large-scale shell-model calculations performed for comparison. These results provide important benchmarks for models that try to describe nuclear shape in neutron-rich nuclei near the magic number N=50.
The purpose of this work is to extend a sample of accurately modeled, benchmark-grade eclipsing binaries (EBs) with accurately determined masses and radii. We select four "well-behaved" Kepler binaries, KIC 2306740, KIC 4076952, KIC 5193386 and KIC 5288543, each with at least eight double-lined spectra from the Apache Point Observatory Galactic Evolution Experiment instrument that is part of the Sloan Digital Sky Surveys III and IV, and from the Hobby–Eberly High Resolution Spectrograph. We obtain masses and radii with uncertainties of 2.5% or less for all four systems. Three of these systems have orbital periods longer than 9 days, and thus populate an undersampled region of the parameter space for extremely well-characterized detached EBs. We compare the derived masses and radii against MESA MIST isochrones to determine the ages of the systems. All systems were found to be coeval, showing that the results are consistent across MESA MIST and PHOEBE .
pH dependent interfacial chemistry depends upon the distribution and respective pKa values of different surface active sites. This is highly relevant to the chemistry of nanoparticle morphologies that expose faces with varying surface termination. Recent synthetic advances for nanoparticles of various minerals, including AlO(OH) (boehmite), present an excellent opportunity to compare and contrast predicted surface pKa on low Miller index planes so as to reinterpret reported interfacial properties (i.e., point of zero charge – PZC) and reactivity. This work employs ab initio molecular dynamics and empirical models to predict site-specific pKa values of accurate (benchmarked) surface models of boehmite. Using the different surface site populations, the PZC is determined and the influence this has upon reported interfacial chemistry is described.
The on-going OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation (MPCMIV) benchmark aims to provide guidance on multi-physics validation through the modelling of two cold ramps. In this paper, the first results for the base irradiation of the father rod and fuel rodlet (refabricated from the father rod), and the first cold ramp are presented. The base irradiation consists of 3 years of irradiation in the Forsmark-2 reactor. The cold ramp encompasses a steady-state pre-ramp period of less than one hour at a low constant linear heat rate (LHR) followed by a ramp test (< 1 min) with a much higher maximal LHR. The base irradiation is modelled using the fuel performance codes FRAPCON and FAST, while the cold ramp modeling is using the fuel performance code FRAPTRAN. Several missing parameters for FRAPCON/FAST base irradiation models have been selected using multiple references such as the OECD/NEA light water reactor Uncertainty Analysis in Modelling (UAM) benchmark specifications and the FRAPCON Integral Assessment report. The obtained results for the base irradiation such as the cladding outer diameter show reasonable agreement with the experimental measurements. The results for the cold ramp show larger differences with the experimental measurements (e.g., cladding axial elongation). However, such differences have been observed as well in other studies involving pellet cladding mechanical interaction analyses and are attributed to the fuel performance modelling assumptions and to the tuned modelling parameters that were not covered by the specifications. Uncertainty and sensitivity analysis might allow a better quantification of these missing parameters. (authors)
Two ocean models are considered for geophysical flow simulations: the multilayer shallow water equations and the multilayer primitive equations. For the former, we investigate the parallel performance of exponential time differencing (ETD) methods, including exponential Rosenbrock–Euler, ETD2wave, and B-ETD2wave. For the latter, we take advantage of the splitting of barotropic and baroclinic modes and propose a new two-level method in which an ETD method is applied to solve the fast barotropic mode. Furthermore, these methods could improve the computational efficiency of numerical simulations because ETD methods allow for much larger time step sizes than traditional explicit time-stepping techniques that are commonly used in existing computational ocean models. Several standard benchmark tests for ocean modeling are performed and comparison of the numerical results demonstrates a great potential of applying the parallel ETD methods for simulating real-world geophysical flows.
This paper presents the modeling and verification of multibody structural dynamics for offshore wind turbines. The flexible tower and support structure of a monopile-based offshore wind turbine are modeled using an acausal, lumped-parameter, multibody approach that incorporates structural flexibility, soil-structure interaction, and hydrodynamic models. Simulation results are benchmarked against alternative modeling approaches, demonstrating the model's ability to accurately capture both static and dynamic behaviors under various wind and wave conditions while maintaining computational efficiency. This work provides a valuable tool for analyzing key structural characteristics of wind turbines, including eigenfrequencies, mode shapes, damping, and internal forces.
Injection of hydraulic fracturing fluid (HFF) into shale formations for unconventional oil/gas production results in chemical reactions in the shale matrix. Our recent experimental study determined the depths to which different types of reactions between the shale matrix and the HFF extended. In the present study, we built continuum-scale reactive transport models to understand the coupling of chemical reactions and the transport of aqueous species in these shale–HFF systems. Calibration of the model with our previous experimental results reveals that it takes hours to months for the shale matrix to completely neutralize the imbibed acids, depending primarily upon the carbonate content of the shale. Both the HFF pH and pore pH affect the location of barite precipitation, resulting in unique barite precipitation profiles extending millimeters into calcite-rich Eagle Ford shale but only tens of micrometers into low-carbonate Marcellus shale. In addition, dissolved oxygen and extracted bitumen are key to reproducing the experimental observation of Fe(III) (oxyhydr)oxide formation in the shale matrix as a result of pyrite dissolution in the shales. A comparison between the modeling results of porosity in the present study to experimentally measured permeabilities in our previous study suggests that chemical reactions occurring at a greater depth than the observable reaction zone might have impacted permeability. Our model serves as a benchmark for efficiently modeling water–rock interactions in similar systems where bulk rock samples react with a solution in batch reactors. Important reactive transport processes were ascertained via modeling, which allows for quantitative prediction of shale–HFF interactions in shale matrices given the shale and HFF compositions.
We introduce a gyrokinetic, linearised Fokker–Planck collision model that satisfies conservation laws and is accurate at arbitrary collisionalities. The differential test-particle component of the operator is exact; the integral field-particle component is approximated using a spherical harmonic and a modified Laguerre polynomial expansion developed by Hirshman and Sigmar (1976 Phys. Fluids 19 1532). The numerical methods of the implementation in the δf-gyrokinetic code stella (Barnes et al 2019 J. Comput. Phys. 391 365–80) are discussed, and conservation properties of the operator are demonstrated. The collision model is then benchmarked against the collision model of the gyrokinetic solver GS2 in the limiting cases of a reduced test-particle collision operator and energy- and momentum-conserving operator. The accuracy of the full collision model is investigated by solving the parallel Spitzer-Härm problem for the transport coefficients. It is shown that retaining collisional energy flux and higher-order terms in the field-particle operator reduces errors in the transport coefficients from 10%–25% for a simple momentum- and energy-conserving model to under 1%.
Large Language Models (LLMs) have shown strong capabilities in general code translation. However, code translation involving parallel programming models remains largely unexplored. This work enhances the capabilities of code LLMs in CUDA-to-SYCL kernel translation with parameter-efficient fine-tuning. The resultant fine-tuned LLM, called ChatPORT, is an effort to provide high-fidelity translations from one programming model to another. We describe the preparation of datasets from heterogeneous computing benchmarks for model fine-tuning and testing, the parameter-efficient fine-tuning of 19 open-source code models ranging in size from 0.5 to 34 billion parameters and evaluate the correctness rates of the SYCL kernels by the fine-tuned models. The experimental results show that most code models fail to translate CUDA codes to SYCL correctly. However, fine-tuning these models using a small set of CUDA and SYCL kernels can enhance the capabilities of these models in kernel translation. Depending on the sizes of the models, the correctness rate ranges from 19.9% to 81.7% for a test dataset of 62 CUDA kernels.
The goal of the eddy current flow meter (ECFM) is to monitor velocities and temperatures of conductive liquid metals. The ECFM can also detect voids in two-phase liquid metal flows. Measurement of these flows can greatly improve the accuracy of the empirical formulas used for fluid dynamics near the reactor core and aid in mapping any non-uniformities in fluid flow such as estimates of temperature and phase. While the eventual goal is to develop the ECFM for the liquid sodium surrounding the Versatile Test Reactor (VTR) core, this report focuses on modeling and experimental validation of ECFM for a moving solid test rod and for liquid mercury in the Target Test Facility (TTF) flow loop to better understand and further develop ECFM measurement capabilities by validating model predictions with benchmark experiments. Eventually the models could be used to design and optimize future ECFMs for specific applications such as monitoring flow within the VTR pool.
This report details the results of building energy modeling analysis evaluating the potential energy savings, economic outcomes, and grid-level electricity reduction associated with cold climate air source heat pump (ccASHP) adoption across multifamily and manufactured housing (MMFH) building typologies in the City and Borough of Juneau (CBJ). Three building archetypes were evaluated: multifamily 4-plex apartments, multifamily 8-plex apartments, and manufactured housing units. Building energy models were developed using OpenStudio-HPXML and calibrated to actual utility consumption data and local meteorological data from the Juneau International Airport weather station using an automated calibration tool following the BPI-2400-S-2015 v.2 standard for model calibration. Occupant behaviors present the greatest variability in successful calibrations. Calibrated models were benchmarked against a baseline electric resistance heating condition, with the selected ccASHP modeled as the retrofit condition and typical meteorological year weather data for all results generation.
In 2020, as part of contract/task order 31310019N0006/31310020F0060, the Nuclear Regulatory Commission tasked Idaho National Laboratory (INL) with benchmarking the MOOSE/GRIZZLY code against the NRC’s Fracture Analysis of Vessels - Oak Ridge (FAVOR), version 16.1 code. Both codes can predict large light-water reactor vessel integrity deterministically and probabilistically. In fact, such predictions are the primary purpose of the FAVOR code, and are a main focus of the GRIZZLY code, although GRIZZLY is capable of modeling a wider range of geometries and problems. The vessel integrity modeling capabilities of the GRIZZLY code are still under development and being gradually expanded, and the capability to model vessel fracture by crack growth has not yet been integrated into GRIZZLY (although it does exist in pre-release versions). Thus, the present benchmark study focused on comparing predictions for the conditional probability of crack growth initiation (CPI) between GRIZZLY and FAVOR v16.1. The present benchmarking study expands on a previous study completed in 2020, which focused on single plate regions, various flaw types, and full vessel studies. The previous study was limited in scope and revealed some relatively large discrepancies, particularly in the case of weld regions. In the present study, detailed investigations into the sources of discrepancies between GRIZZLY and FAVOR were performed, with a focus on weld regions.
The mutual optical intensity (MOI) model is a partially coherent radiation propagation tool that can sequentially simulate beamline optics and provide beam intensity, local degree of coherence and phase distribution at any location along a beamline. This paper extends the MOI model to non-ideal twodimensional (2D) optical systems, such as ellipsoidal and toroidal mirrors with 2D figure errors. Simulation results show that one can tune the trade-off between calculation efficiency and accuracy by varying the number of wavefront elements. The focal spot size of an ellipsoidal mirror calculated with 100 $\times$ 100 elements gives less than 0.4% deviation from that with 250 $\times$ 250 elements, and the computation speed is nearly two orders of magnitude faster. Effects of figure errors on 2D focusing are also demonstrated for a non-ideal ellipsoidal mirror and by comparing the toroidal and ellipsoidal mirrors. Finally, the MOI model is benchmarked against the multi-electron Synchrotron Radiation Workshop (SRW) code showing the model’s high accuracy.
Building energy consumption benchmarking involves challenges associated with various energy patterns for different building types; heating, ventilating, and air-conditioning (HVAC) system types; and climates. Given significant variation in energy use patterns, accurate prediction of long-term energy use using surrogate models remains challenging. Multiple linear regression (MLR) is commonly used for building energy benchmarking because of its simple structure; however, it lacks accuracy compared to other black-box models. Although many studies have compared surrogate models and offer guidance on model selection based on metrics, they do not provide detailed analysis on improving the surrogate model accuracy. In this paper, we implement a surrogate model using polynomial ridge regression (i.e., MLR with interaction terms combined with ridge regularization) for small office and retail strip mall buildings across six HVAC system types and all climate zones, for electricity and natural gas in baseline and proposed scenarios. A simulation workflow is developed using OpenStudio TM /EnergyPlus TM to generate simulation data using measures over a wide range of efficiency inputs. Enhancements based on statistical insights are used for improving the model accuracy using filters, input transformations, and change points. Surrogate models achieved average coefficient of variation of the root mean squared error (CVRMSE) values of 2.17, 1.06, 2.05, and 3.26 for proposed electricity, proposed natural gas, baseline electricity, and baseline natural gas, respectively, with enhancements reducing CVRMSE by an average of 14.9% across all combinations. We provide model interpretation via Shapley additive explanations to determine which input variables most influence energy consumption and provide supportive arguments for enhancements.