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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The application of ICASPA to critical and safe mass calculations - 14586

ICASPA, an Improved Critical and Safe Parameters Algorithm, calculates the size of a fissile body for a given value of k-effective. ICASPA uses an iterative predictor/corrector algorithm in which the MONK9A code is used to derive a precise k-effective value for a given candidate body size; auxiliary equations are then used to adjust the body size. The process is repeated until MONK9A outputs the chosen target value of k-effective. EDF Energy operates eight nuclear power stations comprising one Pressurized Water Reactor (PWR) and seven Advanced Gas-cooled Reactor (AGR) stations. At these sites, the term 'fuel route' is used to encompass all of the ex-reactor arrangements for the handling and storage of fuel. The criticality safety cases for these fuel routes are based on the use of geometrically safe arrangements for the required quantities of fuel. The allowed quantities and arrangements of fuel are safely sub-critical, even under the contingency of accidental moderator ingress. The fuel route safety cases consider all credible potential fault conditions, including events such as dropped fuel. Any such events might change the geometry of the fuel elements, but it is difficult to calculate exact k-effective values for realistic models of dropped fuel. This difficulty is overcome by the use of an alternative approach in which limiting safe masses are calculated for bounding (worst-case) rearrangements of fuel rods and moderators, using geometries similar to those covered by criticality handbook data. Where required, the resulting safe masses are used to set safety case limits and conditions. For example, some fire extinguishants, such as water and ABC dry powder, are also effective moderators. Hence, in some fuel route areas, administrative criticality controls are used to either prohibit or limit the permitted quantities of these materials. This paper describes the work that has been carried out to adopt ICASPA as the approved calculation method for these safe mass calculations. The work has been carried out within the company quality assurance requirements for nuclear safety related software. It has involved the development of a configuration controlled version of ICASPA and the local verification and validation of the resulting code. The benefits from the adoption of ICASPA are also presented. These include accuracy improvements and, because the method uses the MONK9A code for k-effective calculations, the ability to use more sophisticated models for limiting case geometries. (authors)

42 ENGINEERING↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Error Characteristics and Scale Dependence of Current Satellite Precipitation Estimates Products in Hydrological Modeling

Satellite precipitation estimates (SPEs) are promising alternatives to gauge observations for hydrological applications (e.g., streamflow simulation), especially in remote areas with sparse observation networks. However, the existing SPEs products are still biased due to imperfections in retrieval algorithms, data sources and post-processing, which makes the effective use of SPEs a challenge, especially at different spatial and temporal scales. In this study, we used a distributed hydrological model to evaluate the simulated discharge from eight quasi-global SPEs at different spatial scales and explored their potential scale effects of SPEs on a cascade of basins ranging from approximately 100 to 130,000 km 2 . The results indicate that, regardless of the difference in the accuracy of various SPEs, there is indeed a scale effect in their application in discharge simulation. Specifically, when the catchment area is larger than 20,000 km2, the overall performance of discharge simulation emerges an ascending trend with the increase of catchment area due to the river routing and spatial averaging. Whereas below 20,000 km 2 , the discharge simulation capability of the SPEs is more randomized and relies heavily on local precipitation accuracy. Our study also highlights the need to evaluate SPEs or other precipitation products (e.g., merge product or reanalysis data) not only at the limited station scale, but also at a finer scale depending on the practical application requirements. Here we have verified that the existing SPEs are scale-dependent in hydrological simulation, and they are not enough to be directly used in very fine scale distributed hydrological simulations (e.g., flash flood). More advanced retrieval algorithms, data sources and bias correction methods are needed to further improve the overall quality of SPEs.

DTVGM↗
DOE OSTI2018

Focus optimization at relativistic intensity with high numerical aperture and adaptive optics

Improved focusing of laser beams using high numerical aperture systems is an efficient route to increasing intensities in the ultrafast regime to relativistic levels. We experimentally demonstrate a new method of optimizing the focus of a high-power laser, using second harmonic generation at full intensity in a low-pressure gas to provide a figure of merit for optimizing the shape of a deformable mirror via a genetic algorithm. Nonlinear and thermal aberrations are corrected, and aberrations introduced by filters are avoided. Furthermore, the method is applied to focus a millijoule, short pulse (30 fs), high repetition rate laser system to relativistic intensity in both near IR and mid IR regimes.

Lin, Jinpu↗
DOE OSTI2023

A Scalable PDC Placement Technique for Fast and Resilient Monitoring of Large Power Grids

The wide-area measurement system (WAMS) is a key enabler of real-time monitoring of power grids. The essential goals of WAMS design are fast and resilient data transfer from phasor measurement units (PMU) to phasor data concentrators (PDC). We propose a scalable two-stage PDC placement technique for minimizing the end-to-end delay while maintaining resiliency. In the prescreening stage, the plausible candidates of PDC configurations are identified based on a graph theory-based multi-median function (MMF). Here, in this article, a computationally efficient meta-heuristic algorithm is used to address scalability. In the candidate selection stage, two different algorithms, namely, Suurballe's and Dijkstra's, are employed to identify the best of those plausible PDC configurations as the final design. This technique not only minimizes the hop paths between PMUs and PDCs, but also ensures network resiliency against single PMU, PDC, or communication link failure by incorporating the roles of PMUs in power grid observability into routing policy. Simulation results on the IEEE 57-bus test power system and the 2000-bus test power system demonstrate the effectiveness and scalability of the proposed technique.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Automated size-specific CT dose monitoring program: Assessing variability in CT dose

Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED{sub adj}). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED{sub adj} between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED{sub adj} that differed by up to 44% from effective dose estimates that were not adjusted by patient size. Additionally, considerable differences were noted in ED{sub adj} distributions between scanners, with scanners employing iterative reconstruction exhibiting significantly lower ED{sub adj} (range: 9%-64%). Finally, a significant difference (up to 59%) in ED{sub adj} distributions was observed between institutions, indicating the potential for dose reduction. Conclusions: The authors developed a robust automated size-specific radiation dose monitoring program for CT. Using this program, significant differences in ED{sub adj} were observed between scanner models and across institutions. This new dose monitoring program offers a unique tool for improving quality assurance and standardization both within and across institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region

Highlights: • We developed an optimization model to minimize cost of infectious waste management. •Two different software were used for model solution. • Model optimizes locations and capacities of treatment plants and transfer stations. • The higher percentage of total cost was due to construction of the treatment plant. • Sensitivity analysis with respect to fuel cost and waste production was conducted. - Abstract: The objective of this work was to develop an optimization model to minimize the cost of a collection, haul, transfer, treatment and disposal system for infectious medical waste (IMW). The model calculates the optimum locations of the treatment facilities and transfer stations, their design capacities (t/d), the number and capacities of all waste collection, transport and transfer vehicles and their optimum transport path and the minimum IMW management system cost. Waste production nodes (hospitals, healthcare centers, peripheral health offices, private clinics and physicians in private practice) and their IMW production rates were specified and used as model inputs. The candidate locations of the treatment facilities, transfer stations and sanitary landfills were designated, using a GIS-based methodology. Specifically, Mapinfo software with exclusion criteria for non-appropriate areas was used for siting candidate locations for the construction of the treatment plant and calculating the distance and travel time of all possible vehicle routes. The objective function was a non-linear equation, which minimized the total collection, transport, treatment and disposal cost. Total cost comprised capital and operation costs for: (1) treatment plant, (2) waste transfer stations, (3) waste transport and transfer vehicles and (4) waste collection bins and hospital boxes. Binary variables were used to decide whether a treatment plant and/or a transfer station should be constructed and whether a collection route between two or more nodes should be followed. Microsoft excel software was used as installation platform of the optimization model. For the execution of the optimization routine, two completely different software were used and the results were compared, thus, resulting in higher reliability and validity of the results. The first software was Evolver, which is based on the use of genetic algorithms. The second one was Crystal Ball, which is based on Monte Carlo simulation. The model was applied to the Region of East Macedonia – Thrace in Greece. The optimum solution resulted in one treatment plant located in the sanitary landfill area of Chrysoupolis, required no transfer stations and had a total management cost of 38,800 €/month or 809 €/t. If a treatment plant is sited in the most eastern part of the Region, i.e., the industrial area of Alexandroupolis, the optimum solution would result in a transfer station of 23 m{sup 3}, located near Kavala General Hospital, and a total cost of 39,800 €/month or 831 €/t. A sensitivity analysis was conducted and two alternative scenarios were optimized. In the first scenario, a 15% rise in fuel cost and in the second scenario a 25% rise in IMW production were considered. At the end, a cost calculation in €/t/km for every type of vehicle used for haul and transfer was conducted. Also, the cost of the whole system was itemized and calculated in €/t/km and €/t. The results showed that the higher percentage of the total cost was due to the construction of the treatment plant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Material transfers detection with seismic observations

We are exploring the use of data from a seismic network around a research nuclear reactor and isotope production facility at Oak Ridge National Laboratory to study activity patterns related to the transfer of nuclear material. A sensor network with eight seismometers was installed around the High Flux Isotope Reactor and the Radiochemical Engineering Development Center and started operating in October 2019. These data are used to detect and characterize operational events around facility. We are using those data to extract signals related to the movement of vehicles involved in the transport of nuclear materials (e.g., transportation of reactor fuel, targets, and product isotopes). Large vehicles produce mechanical energy that can be observed as seismic signals, either as the result of sound emanating from the vehicle engine or by the generation of surface waves as a response of the ground to the load of the vehicles. In particular, the station located near the entrance gate of the facility displays a clear seismic signature as vehicles cross a metal platform on the ground. This signal is characterized by sharp energy bursts that correspond to the number of axles on the vehicle. We developed and are testing an algorithm to identify sequences of energy bursts to count and characterize vehicles of different sizes. We are also exploring the use of seismic polarization analysis to measure the degree of polarization of the observed signals. These two techniques for detection and characterization of vehicles used for nuclear material transfers will be validated with seismic data from a targeted collection using different vehicles and routes similar to the ones used in real-life scenarios at the High Flux Isotope Reactor.

Marcillo, Omar↗
DOE OSTI2021

Hybrid MEMS-CMOS ion traps for NISQ computing

Surging interest in engineering quantum computers has stimulated significant and focused research on technologies needed to make them manufacturable and scalable. In the ion trap realm this has led to a transition from bulk three-dimensional macro-scale traps to chip-based ion traps and included important demonstrations of passive and active electronics, waveguides, detectors, and other integrated components. At the same time as these technologies are being developed the system sizes are demanding more ions to run noisy intermediate scale quantum (NISQ) algorithms, growing from around ten ions today to potentially a hundred or more in the near future. To realize the size and features needed for this growth, the geometric and material design space of microfabricated ion traps must expand. In this paper we describe present limitations and the approaches needed to overcome them, including how geometric complexity drives the number of metal levels, why routing congestion affects the size and location of shunting capacitors, and how RF power dissipation can limit the size of the trap array. Finally, we also give recommendations for future research needed to accommodate the demands of NISQ scale ion traps that are integrated with additional technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Rapid prototyping of arbitrary 2D and 3D wireframe DNA origami

Wireframe DNA origami assemblies can now be programmed automatically from the top-down using simple wireframe target geometries, or meshes, in 2D and 3D, using either rigid, six-helix bundle (6HB) or more compliant, two-helix bundle (DX) edges. While these assemblies have numerous applications in nanoscale materials fabrication due to their nanoscale spatial addressability and high degree of customization, no easy-to-use graphical user interface software yet exists to deploy these algorithmic approaches within a single, standalone interface. Further, top-down sequence design of 3D DX-based objects previously enabled by DAEDALUS was limited to discrete edge lengths and uniform vertex angles, limiting the scope of objects that can be designed. Here, we introduce the open-source software package ATHENA with a graphical user interface that automatically renders single-stranded DNA scaffold routing and staple strand sequences for any target wireframe DNA origami using DX or 6HB edges, including irregular, asymmetric DX-based polyhedra with variable edge lengths and vertices demonstrated experimentally, which significantly expands the set of possible 3D DNA-based assemblies that can be designed. ATHENA also enables external editing of sequences using caDNAno, demonstrated using asymmetric nanoscale positioning of gold nanoparticles, as well as providing atomic-level models for molecular dynamics, coarse-grained dynamics with oxDNA, and other computational chemistry simulation approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Delayed HIV diagnosis common in Sweden, 2003–2010

Background: Early diagnosis of HIV is important for the prognosis of individual patients, because antiretroviral treatment can be started at the appropriate time, and for public health, because transmission can be prevented. Methods: Data were collected from 767 HIV patients who were diagnosed in Sweden during 2003–2010 and were infected in Sweden or born in Sweden and infected abroad. A recent infection testing algorithm (RITA) was applied to BED-EIA test results (OD-n < 0.8), CD4 counts (≥ 200 cells/μl), and clinical information. A recent infection classification was used as indicator for early diagnosis. Time trends in early diagnosis were investigated to detect population changes in HIV testing behavior. Patients with early diagnosis were compared to patients with delayed diagnosis with respect to age, gender, transmission route, and country of infection (Sweden or abroad). Results: Early diagnosis was observed in 271 patients (35%). There was no statistically significant time trend in the yearly percentage of patients with early diagnosis in the entire study group (p = 0.836) or in subgroups. Early diagnosis was significantly more common in men who have sex men (MSM) (45%) than in heterosexuals (21%) and injecting drug users (27%) (p < 0.001 and p = 0.001, respectively) in both univariate and multivariable analyses. The only other factor that remained associated with early diagnosis in multivariable analysis was young age group. Conclusion: Approximately one-third of the study patients were diagnosed early with no significant change over time. Delayed HIV diagnosis is a considerable problem in Sweden, which does not appear to diminish.

delayed diagnosis↗
DOE OSTI2015

Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are demonstrated in a physically realistic Brownian coagulation case. The computational accuracy is validated with benchmark solution of discrete-sectional method. The simulation results show that the comprehensive approach can attain very favorable improvement in cost without sacrificing computational accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Harmonic analysis of discrete tracers of large-scale structure

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions. We compare and contrast the approaches to this problem taken in the cosmic microwave background and large-scale structure communities, and advocate for a direct approach that avoids pixelization. We describe a method for performing a pseudo-spectrum analysis of a galaxy data set and show that it can be implemented efficiently using well-known algorithms for special functions that are suited to acceleration by graphics processing units (GPUs). The method returns the same spectra as the more traditional map-based approach if in the latter the number of pixels is taken to be sufficiently large and the mask is well sampled. The method is readily generalizable to cross-spectra and higher-order functions. It also provides a convenient route for distributing the information in a galaxy catalog directly in harmonic space, as a complement to releasing the configuration-space positions and weights, and a route to spectral apodization. Finally, we make public a code enabling the application of our method to existing and upcoming datasets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Deploying Mobility-On-Demand for All by Optimizing Paratransit Services

While on-demand ride-sharing services have become popular in recent years, traditional on-demand transit services cannot be used by everyone, e.g., people who use wheelchairs. Paratransit services, operated by public transit agencies, are a critical infrastructure that offers door-to-door transportation assistance for individuals who face challenges in using standard transit routes. However, with declining ridership and mounting financial pressure, public transit agencies in the USA struggle to operate existing services. We collaborate with a public transit agency from the southern USA, highlight the specific nuances of paratransit optimization, and present a vehicle routing problem formulation for optimizing paratransit. We validate our approach using real-world data from the transit agency, present results from an actual pilot deployment of the proposed approach in the city, and show how the proposed approach comprehensively outperforms existing approaches used by the transit agency. To the best of our knowledge, this work presents one of the first examples of using open-source algorithmic approaches for paratransit optimization.

Pavia, Sophie↗
DOE OSTI2014

Trip Prediction Using GIS for Vehicle Energy Efficiency

In this paper, we present a novel trip prediction process whose main applications include vehicle energy efficiency optimization. The process is composed of multiple parts. First, a Markov chain model is built from quality-checked, real-world vehicle speed data. Secondly, a geographical information system (GIS), ADAS-RP, is used to define a real-world itinerary on a map-based interface. Finally, an algorithm runs the Markov chains under constraints from the GIS. As a result, any number of second-by-second stochastic speed profiles can be generated for a given itinerary. These speed profiles can then be inputs to vehicle powertrain models such as Autonomie, which can be used to predict energy consumption and other operational parameters. An example of the application of speed prediction is also described, involving route-based energy management for plug-in hybrid electric vehicles, in which the knowledge of future speed profiles can be used to find the optimal energy split.

energy efficiency↗
DOE OSTI2013

Minimising the error in eigenvalue calculations involving the Boltzmann transport equation using goal-based adaptivity on unstructured meshes

This article presents a method for goal-based anisotropic adaptive methods for the finite element method applied to the Boltzmann transport equation. The neutron multiplication factor, k{sub eff}, is used as the goal of the adaptive procedure. The anisotropic adaptive algorithm requires error measures for k{sub eff} with directional dependence. General error estimators are derived for any given functional of the flux and applied to k{sub eff} to acquire the driving force for the adaptive procedure. The error estimators require the solution of an appropriately formed dual equation. Forward and dual error indicators are calculated by weighting the Hessian of each solution with the dual and forward residual respectively. The Hessian is used as an approximation of the interpolation error in the solution which gives rise to the directional dependence. The two indicators are combined to form a single error metric that is used to adapt the finite element mesh. The residual is approximated using a novel technique arising from the sub-grid scale finite element discretisation. Two adaptive routes are demonstrated: (i) a single mesh is used to solve all energy groups, and (ii) a different mesh is used to solve each energy group. The second method aims to capture the benefit from representing the flux from each energy group on a specifically optimised mesh. The k{sub eff} goal-based adaptive method was applied to three examples which illustrate the superior accuracy in criticality problems that can be obtained.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Engine-in-the-Loop Study of a Hierarchical Predictive Online Controller for Connected and Automated Heavy-Duty Vehicles

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. This work is experimentally experimentally validated via a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve the closed-loop validation of the proposed control strategies, both individually and combined. These studies show that this hierarchy of algorithms is capable of running online, with the round-trip communication delay inherent in EIL simulation being one of the key factors affecting the EIL results. Moreover, the EIL studies are encouraging, both in terms of the successful hierarchical integration of the underlying algorithms and also in the resulting fuel savings seen in the EIL tests. In particular, the EIL results suggest that an aggressive overall goal of reducing vehicle fuel consumption by 15-20% or more is potentially achievable, especially in urban/suburban scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Quantum-classical embedding via ghost Gutzwiller approximation for enhanced simulations of correlated electron systems

Simulating correlated materials on present-day quantum hardware remains challenging due to limited quantum resources. Quantum embedding methods offer a promising route by reducing computational complexity through the mapping of bulk systems onto effective impurity models, allowing more feasible simulations on pre- and early-fault-tolerant quantum devices. Here, this work develops a quantum-classical embedding framework based on the ghost Gutzwiller approximation to enable quantum-enhanced simulations of ground-state properties and spectral functions of correlated electron systems. Circuit complexity is analyzed using an adaptive variational quantum algorithm on a statevector simulator, applied to the infinite-dimensional Hubbard model with increasing ghost mode numbers from 3 to 5, resulting in circuit depths growing from 16 to 104. Noise effects are examined using a realistic error model, revealing significant impact on the spectral weight of the Hubbard bands. To mitigate these effects, the Iceberg quantum error detection code is employed, achieving up to 40% error reduction in simulations. Finally, the accuracy of the density matrix estimation and the derived spectral function is benchmarked on IBM and Quantinuum quantum hardware, featuring distinct qubit-connectivity and employing multiple levels of error mitigation techniques.

Chen, I-Chi [Ames Laboratory (AMES), Ames, IA (Uni↗