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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Need A Boost? A Comparison of Traditional Commuting Models with the XGBoost Model for Predicting Commuting Flows

Commuting models estimate the number of commuting trips from home to work locations in a given area. Since their infancy, they have been increasingly used in a variety of fields to reduce traffic and pollution, drive infrastructure choices, and solve a variety of other problems. Traditional commuting models, such as gravity and radiation models, typically have a strict structural form and limited number of input variables, which may limit their ability to predict commuting flows as well as machine learning models that might better capture the complex dynamics of the commuting process. To determine whether machine learning models might add value to the field of commuter flow prediction, we compare and discuss the performance of two standard traditional models with the XGBoost machine learning algorithm for predicting home to work commuter flows from a well-known United States commuting dataset. We find that the XGBoost model outperforms the traditional models on three commonly used metrics, indicating that machine learning models may add value to the field of commuter flow prediction.

Morton, April↗
DOE OSTI2018

On OM-decomposable sets

We introduce and study the family of sets in a finite-dimensional Euclidean space which can be written as the Minkowski sum of an open, bounded, and convex set and a closed convex cone. We establish several properties of the class of such sets, called OM-decomposable, some of which extend related properties holding for the class of Motzkin decomposable sets (i.e., those for which the convex and bounded set in the decomposition is requested to be closed, hence compact).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

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↗
DOE OSTI2021

Autonomous Ride-Share Fleet to Reduce Traffic Congestion for Suburban Commuters

As urbanization progresses in areas across the United States, traffic is worsening as more personal vehicles are required to ferry suburban commuters between home and work. Many suburban commuters would prefer public transportation over driving a personal vehicle to use their commute time more efficiently, but existing infrastructure can make conventional public transit inconvenient or impossible. There is a need for a wide-spread system that can safely, conveniently, and cost-effectively transport suburban commuters to and from work. This will decrease congestion on roads, allowing suburban areas to continue growing in population without dramatically increasing commute times. The customer (suburban commuters) needs a system that enables them to commute to and from work more efficiently. This efficiency can be thought of as both the total time spent commuting, as well as the quality of that time spent commuting. The “quality” of the time is subjective, but in general is a metric of the ability of the commuter to focus on things other than traveling during the commute process. The new system should decrease the total time commuting, but increase the quality of the commute time. Collectively Americans spend a total of 55.2 minutes per day commuting, up from 43.4 minutes per day in 1980. Additionally, as of 2013, 76% of Americans get to work by driving alone, up from 64% in 19803. The 40-hour work-week was established in the U.S in 1940 and has not changed since. The result is that Americans spend an increasing amount of time commuting and at a lower quality, but the standard work week has not changed. This decreases the amount of time adults in the U.S have for leisure, friends, and family. A system solution has the potential to improve this, particularly with the advent of new and future technologies. This system is picked specifically for suburban commuters, as they have the highest potential to be helped.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The impact of autonomous vehicles on commute ridesharing with uncertain work end time

The uncertainty in work end time can prevent ridesharing between two commuters with identical home and work locations. This effect can be alleviated by autonomous vehicles (AV): when two commuters share a ride from home to work, if the realized work end times result in a long wait between the two, an additional AV can be easily repositioned from home to work, whereas with regular human-driven vehicles one has to either bear the long wait or request expensive taxi service. This observation implies that AVs have great potential for increasing commute ridesharing. To study this effect, we develop evening commute bottleneck models with uncertain work end time and establish mode choice equilibrium for the round-trip commute. We find that, with regular vehicles, because of the expected waiting cost caused by work end time uncertainty, commuters typically do not share rides even though they have the same home and work locations. With AVs, commuters always share rides for the morning commute, and they also share rides for the evening commute if their work end times turn out to be close; otherwise, they reposition an additional AV to pick one of them up. Finally, our numerical examples show that AVs can encourage commute ridesharing and significantly reduce the expected round-trip travel costs for commuters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unlocking nighttime mobility: Land use and accessibility in public transit for night commuters

Night commuters are integral to urban transportation systems. Essential services such as healthcare and manufacturing rely on workers who travel at night, and reliable mobility options are crucial for them. A gap exists in understanding how land use and accessibility influence public transportation use among night commuters. This study addresses this gap by using public data to explore land use and accessibility factors that affect night commuters' public transportation use in New York State. We investigated (1) the demographic characteristics of night commuters; (2) the influence of land use and accessibility on nighttime public transportation use; and (3) potential improvements to increase public transportation use and their impact. We combined data from the National Household Travel Survey with the Smart Location Database to link home locations with land use characteristics. Using logistic regression, we found that although females are generally less likely to be night commuters, they are more likely to use public transportation. Longer commute distances are associated with higher use of public transportation. Increasing job density along fixed-guideway transit routes and improving overall job accessibility via public transportation significantly enhances public transportation use among night commuters. In conclusion, this research provides actionable insights for public transportation agencies and urban planners to support night commuters, improving access and encouraging nighttime employment.

Job accessibility↗
DOE OSTI2025

CAML: Commutative Algebra Machine Learning─A Case Study on Protein–Ligand Binding Affinity Prediction

Recently, Suwayyid and Wei introduced commutative algebra as an emerging paradigm for machine learning and data science. In this work, we propose commutative algebra machine learning (CAML) for the prediction of protein−ligand binding affinities. Specifically, we apply persistent Stanley−Reisner theory, a key concept in combinatorial commutative algebra, to the affinity predictions of protein−ligand binding and metalloprotein−ligand binding. We present three new algorithms, i.e., element-specific commutative algebra, category-specific commutative algebra, and commutative algebra on bipartite complexes, to tackle the complexity of data involved in (metallo) protein−ligand complexes. We show that the proposed CAML outperforms other state-of-theart methods in (metallo) protein−ligand binding affinity predictions, indicating the great potential of commutative algebra learning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mitigating commutation failures in HVDC systems with SFCL deployment

Commutation failures represent a prevalent issue encountered in line-commutated-converter high voltage direct current (LCC-HVDC) systems. As the widespread deployment of HVDC systems continues, the risk associated with commutation failures increases, posing a growing threat to power grids due to their potential to trigger severe consequences, including cascading failures and widespread blackouts. This research paper aims to address the significant issue of commutation failure within direct current (DC) systems through advocating for the use of resistive-type Superconducting Fault Current Limiters (R-SFCLs). To substantiate the efficacy of this proposed strategy, an array of simulations are executed using the PSCAD/EMTDC software. This comprehensive study investigates the performance characteristics of R-SFCLs configured with varying resistance values, scrutinizing their response under diverse fault resistance scenarios and distinct fault initiation times within the LCC-HVDC system. The outcomes of these simulations are that SFCLs confer significant advantages for mitigating commutation failures, surpassing traditional mitigation methods in terms of effectiveness. Consequently, SFCLs emerge as an optimal solution to prevent commutation failures in the HVDC systems.

Commutation failure↗
DOE OSTI2023

Analysis and Characterization of Four-quadrant Switches based Commutation Cell

A four-quadrant switch (FQS) blocks either polarity voltage and controls current flow in both directions. Unlike voltage-source converters, in which two-quadrant switches operate over a narrow voltage range, four-quadrant switches are required to operate over a wide range of both voltage and current in applications such as matrix converters and current-source converters. Furthermore, matrix converters require multi-step commutation schemes compared to two-step schemes for current-bidirectional switch based voltage-source converters and voltage-bidirectional switch based current-source converters. This paper provides a generalized overview of commutation schemes used for two and four quadrant switches based two-level commutation cells, identifies comparison indices for FQS commutation schemes, and discusses the need for adaptive commutation-step times for wide voltage and current variation applications. Also, the static and dynamic characteristics of 1.2 kV rated FQS implementations utilizing commercial SiC MOSFETs from four different manufacturers and novel monolithic SiC BiDirectional Field Effect Transistor (BiDFET) have been reported.

Commutation cell, four quadrant switch, SiC Bidire↗
DOE OSTI2022

A High-Accuracy Power Loss Model of SiC MOSFETs in Current Source Inverter Considering Current Commutation and Parasitic Parameters

Power loss estimation of power electronic devices is important to the efficiency optimization of motor drives used in many applications. However, most existing simplified power loss models of silicon carbide (SiC) MOSFETs are not sufficiently accurate due to their neglect of parasitic parameters in the current commutation loop. In addition, the loss model of the voltage source inverter (VSI) cannot be directly applied to the current source inverter (CSI) because of differences between their commutation loops. First, the commutation processes for VSIs and CSIs are compared. The voltage and current trajectories of SiC MOSFETs in the switching transition of a CSI-based motor drive system are analyzed in detail. Based on these results, the conduction and switching losses of SiC MOSFETs in CSIs are modeled considering the current commutation details. In addition, the proposed analytical model includes parasitic inductances and capacitances in the current commutation loop. Experimental results have verified that the proposed power loss model delivers higher accuracy loss predictions than the conventional loss model.

current commutation, current source inverter, powe↗
DOE OSTI2017

Projected Commutator DIIS Method for Accelerating Hybrid Functional Electronic Structure Calculations

The commutator direct inversion of the iterative subspace (commutator DIIS or C-DIIS) method developed by Pulay is an efficient and the most widely used scheme in quantum chemistry to accelerate the convergence of self-consistent field (SCF) iterations in Hartree–Fock theory and Kohn–Sham density functional theory. The C-DIIS method requires the explicit storage of the density matrix, the Fock matrix, and the commutator matrix. Hence, the method can only be used for systems with a relatively small basis set, such as the Gaussian basis set. We develop a new method that enables the C-DIIS method to be efficiently employed in electronic structure calculations with a large basis set such as planewaves for the first time. The key ingredient is the projection of both the density matrix and the commutator matrix to an auxiliary matrix called the gauge-fixing matrix. The resulting projected commutator-DIIS method (PC-DIIS) only operates on matrices of the same dimension as that consists of Kohn–Sham orbitals. The cost of the method is comparable to that of standard charge mixing schemes used in large basis set calculations. The PC-DIIS method is gauge-invariant, which guarantees that its performance is invariant with respect to any unitary transformation of the Kohn–Sham orbitals. We demonstrate that the PC-DIIS method can be viewed as an extension of an iterative eigensolver for nonlinear problems. We use the PC-DIIS method for accelerating Kohn–Sham density functional theory calculations with hybrid exchange–correlation functionals, and demonstrate its superior performance compared to the commonly used nested two-level SCF iteration procedure. Furthermore, we demonstrate that in the context of ab initio molecular dynamics (MD) simulation with hybrid functionals one can extrapolate the gauge-fixing matrix to achieve the goal of extrapolating the entire density matrix implicitly along the MD trajectory. Here, numerical results indicate that the new method significantly reduces the number of SCF iterations per MD step, compared to the commonly used strategy of extrapolating the electron density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Geometric properties of commutative subalgebras of partial differential operators

We investigate further algebro-geometric properties of commutative rings of partial differential operators, continuing our research started in previous articles. In particular, we start to explore the simplest and also certain known examples of quantum algebraically completely integrable systems from the point of view of a recent generalization of Sato's theory, developed by the first author. We give a complete characterization of the spectral data for a class of 'trivial' commutative algebras and strengthen geometric properties known earlier for a class of known examples. We also define a kind of restriction map from the moduli space of coherent sheaves with fixed Hilbert polynomial on a surface to an analogous moduli space on a divisor (both the surface and the divisor are part of the spectral data). We give several explicit examples of spectral data and corresponding algebras of commuting (completed) operators, producing as a by-product interesting examples of surfaces that are not isomorphic to spectral surfaces of any (maximal) commutative ring of partial differential operators of rank one. Finally, we prove that any commutative ring of partial differential operators whose normalization is isomorphic to the ring of polynomials k[u,t] is a Darboux transformation of a ring of operators with constant coefficients. Bibliography: 39 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Modular Commutators in Conformal Field Theory

The modular commutator is a recently discovered entanglement quantity that quantifies the chirality of the underlying many-body quantum state. In this Letter, we derive a universal expression for the modular commutator in conformal field theories in 1 + 1 dimensions and discuss its salient features. We show that the modular commutator depends only on the chiral central charge and the conformal cross ratio. We test this formula for a gapped (2 + 1)-dimensional system with a chiral edge, i.e., the quantum Hall state, and observe excellent agreement with numerical simulations. Furthermore, we propose a geometric dual for the modular commutator in certain preferred states of the AdS/CFT correspondence. Finally, for these states, we argue that the modular commutator can be obtained from a set of crossing angles between intersecting Ryu-Takayanagi surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Commuter Assistance Program Administrative Operating Procedure

Sandia National Laboratories/New Mexico’s (SNL/NM) Commuter Assistance Program (CAP) offers commuting alternatives to driving a single-occupant vehicle (SOV) to members of the workforce (MOW). The goal of this program is to reduce SOV use for commuting to and from SNL/NM, provide MOW opportunities to reduce their transportation costs, reduce greenhouse gas emissions, and reduce parking congestion at SNL/NM. The CAP advocates alternative transportation strategies such as carpooling, vanpooling, bicycling, and using public transportation. The Commuter Assistance Program website is the portal for MOW to access information about the different commuting alternatives available. Additionally, the website provides information on the City of Albuquerque’s Park and Ride program, traffic conditions, and the City of Albuquerque’s Guaranteed Ride Home.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Preliminary Routing for a National Laboratory Lab-Wide Commuting Program

There is a growing interest in reducing the amount of vehicle miles traveled (VMT), both in public and private sector organizations, in an effort to reduce overall carbon emissions. The Oak Ridge National Laboratory (ORNL), located in Oak Ridge, Tennessee, and located within close proximity to Knoxville, Tennessee, has more than 4,500 employees, most of which live in and around Knoxville. ORNL is currently developing a pilot commuting program for all employees, which incorporates the use of park-and-ride facilities. This study outlines the methodology behind the preliminary geoanalysis and routing used in developing a lab-wide commuting program. Due to privacy concerns, the data used for the study included numbers of employee residences per zip code rather than actual residential addresses. Commuting configurations by clustered zip code area and vehicle type were developed based on number of residences in a limited area, and the desire to minimize VMT. Central locations were selected using ArcGIS software. Satellite imagery was used to locate actual, suitable parking facilities to accommodate the specified number of residents involved in each commuting configuration. Optimized routing, and estimations of travel times, were performed using TransCAD GIS software. Energy estimates in kilowatt-hours (kwh) and gallons of gasoline, and gallons of gasoline equivalent, were all determined based on the scenarios. Standard petroleum-fueled vehicles were used in the initial estimates. Standard electric vehicles were also used in alternative scenarios to estimate potential additional energy and fuel savings. Furthermore the initial findings from this work will be used to develop a pilot program for ORNL.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Cyclist exposure to black carbon, ultrafine particles and heavy metals: An experimental study along two commuting routes near Antwerp, Belgium

Highlights: • Wearable UFP and BC instrumentation was carried along whilst cycling 2 different commuting routes. • HR-ICP-MS provided elemental information on railway- and roadside-exposed routes. • Heart rate was tracked simultaneously to estimate the personal inhaled pollutant dose. • The bicycle highway route exhibited 300% lower BC and 20% lower UFP concentrations. • Elemental differences are observed between the considered commuting routes. Urban environments typically exhibit large atmospheric pollution variation, in both space and time. In contrast to traditional monitoring networks suffering from a limited spatial coverage, mobile platforms enable personalized high-resolution monitoring, providing valuable insights into personal atmospheric pollution exposure, and the identification of potential pollution hotspots. This study evaluated personal cyclist exposure to UFPs, BC and heavy metals whilst commuting near Antwerp, Belgium, by performing mobile measurements with wearable black carbon (BC) and ultrafine particle (UFP) instruments. Loaded micro-aethalometer filterstrips were chemically analysed and the inhaled pollutant dose determined from the exhibited heart rate. Considerable spatial pollutant variation was observed along the travelled routes, with distinct contributions from spatial factors (e.g. traffic intersections, urban park and market) and temporary events. On average 300% higher BC, 20% higher UFP and changing elemental concentrations are observed along the road traffic route (RT), when compared to the bicycle highway route (BH). Although the overall background pollution determines a large portion of the experienced personal exposure (in this case 53% for BC and 40% for UFP), cyclists can influence their personal atmospheric pollution exposure, by selecting less exposed commuting routes. Our results, hereby, strengthen the body of evidence in favour of further policy investments in isolated bicycle infrastructure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.↗