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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Non-Markovian dynamics of a superconducting qubit in an open multimode resonator

In this work, we study the dynamics of a transmon qubit that is capacitively coupled to an open multimode superconducting resonator. Our effective equations are derived by eliminating resonator degrees of freedom while encoding their effect in the Green's function of the electromagnetic background. We account for the dissipation of the resonator exactly by employing a spectral representation for the Green's function in terms of a set of non-Hermitian modes and show that it is possible to derive effective Heisenberg-Langevin equations without resorting to the rotating-wave, two-level, Born, or Markov approximations. A well-behaved time-domain perturbation theory is derived to systematically account for the nonlinearity of the transmon. We apply this method to the problem of spontaneous emission, capturing accurately the non-Markovian features of the qubit dynamics, valid for any qubit-resonator coupling strength.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Increasing Flexibility in Energy Code Compliance: Performance Packages

Energy codes and standards have provided significant increases in building efficiency over the last 38 years, since the first national energy code was published in late 1975. The most commonly used path in energy codes, the prescriptive path, appears to be reaching a point of diminishing returns. As the code matures, the prescriptive path becomes more complicated, and also more restrictive. It is likely that an approach that considers the building as an integrated system will be necessary to achieve the next real gains in building efficiency. Performance code paths are increasing in popularity; however, there remains a significant design team overhead in following the performance path, especially for smaller buildings. This paper focuses on development of one alternative format, prescriptive packages. A method to develop building-specific prescriptive packages is reviewed based on a multiple runs of prototypical building models that are used to develop parametric decision analysis to determines a set of packages with equivalent energy performance. The approach is designed to be cost-effective and flexible for the design team while achieving a desired level of energy efficiency performance. A demonstration of the approach based on mid-sized office buildings with two HVAC system types is shown along with a discussion of potential applicability in the energy code process.

Hart, Philip R.↗
DOE OSTI2015

Increasing Flexibility in Energy Code Compliance: Performance Packages

Energy codes and standards have provided significant increases in building efficiency over the last 38 years, since the first national energy code was published in late 1975. The most commonly used path in energy codes, the prescriptive path, appears to be reaching a point of diminishing returns. As the code matures, the prescriptive path becomes more complicated, and also more restrictive. It is likely that an approach that considers the building as an integrated system will be necessary to achieve the next real gains in building efficiency. Performance code paths are increasing in popularity; however, there remains a significant design team overhead in following the performance path, especially for smaller buildings. This paper focuses on development of one alternative format, prescriptive packages. A method to develop building-specific prescriptive packages is reviewed based on a multiple runs of prototypical building models that are used to develop parametric decision analysis to determines a set of packages with equivalent energy performance. The approach is designed to be cost-effective and flexible for the design team while achieving a desired level of energy efficiency performance. A demonstration of the approach based on mid-sized office buildings with two HVAC system types is shown along with a discussion of potential applicability in the energy code process.

Hart, Reid↗
DOE OSTI2022

Social Disparities of Pain and Pain Intensity Among Women Diagnosed With Early Stage Breast Cancer

Background: Breast cancer is one of the most commonly diagnosed cancers among women in the United States and pain is the most common side effect of breast cancer and its treatment. Yet, the relationships between social determinants of pain and pain experience/intensity remain under-investigated. We examined the associations between social determinants of pain both at the individual level and the neighborhood level to understand how social conditions are associated with pain perception among early stage breast cancer patients. Methods: We conducted integrated statistical analysis of 1,191 women with early stage breast cancer treated at a large cancer center in Memphis, Tennessee. Combining electronic health records, patient-reported data and census data regarding residential address at the time of first diagnosis, we evaluated the relationships between social determinants and pain perception. Pain responses were self-reported by a patient as a numerical rating scale score at the patient’s initial diagnosis and follow-up clinical visits. We implemented two sets of statistical analyses of the zero-inflated Poisson model and estimated the associations between neighborhood poverty prevalence and breast cancer pain intensity. After adjustment for demographic characteristics, cancer stage, and chemotherapy, pain perception was significantly associated with poverty and blight level of the neighborhood. Results: Among women living in the highest-poverty areas, the odds of reporting pain were 2.48 times higher than those in the lowest-poverty area. Women living in the highest-blight area had 5.43 times higher odds of reporting pain than those in the lowest-blight area. Neighborhood-level social determinants were significantly associated with pain intensity among women diagnosed with early-stage breast cancer. Conclusions: Distressed neighborhood conditions are significantly associated with higher pain perception. Breast cancer patients living in socio-economically disadvantaged neighborhoods and in poor environmental conditions reported higher pain severity compared to patients from less distressed neighborhoods. Therefore, post-diagnosis pain treatment design needs to be tailored to the social determinants of the breast cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Confidence in Numerical Simulations

This PowerPoint presentation offers a high-level discussion of uncertainty, confidence and credibility in scientific Modeling and Simulation (M&S). It begins by briefly evoking M&S trends in computational physics and engineering. The first thrust of the discussion is to emphasize that the role of M&S in decision-making is either to support reasoning by similarity or to “forecast,” that is, make predictions about the future or extrapolate to settings or environments that cannot be tested experimentally. The second thrust is to explain that M&S-aided decision-making is an exercise in uncertainty management. The three broad classes of uncertainty in computational physics and engineering are variability and randomness, numerical uncertainty and model-form uncertainty. The last part of the discussion addresses how scientists “think.” This thought process parallels the scientific method where by a hypothesis is formulated, often accompanied by simplifying assumptions, then, physical experiments and numerical simulations are performed to confirm or reject the hypothesis. “Confidence” derives, not just from the levels of training and experience of analysts, but also from the rigor with which these assessments are performed, documented and peer-reviewed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Reaction Profiles and Kinetics for Radical–Radical Hydrogen Abstraction via Multireference Coupled Cluster Theory

Radical-radical abstractions in hydrocarbon oxidation chemistry are disproportionation reactions that are generally exothermic with little or no barrier yet are underappreciated and poorly studied. Such challenging multireference electronic structure problems are tackled here using the recently developed state-specific multireference coupled cluster methods Mk-MRCCSD and Mk-MRCCSD(T), as well as the companion perturbation theory Mk-MRPT2 and the established MRCISD, MRCISD+Q, and CASPT2 approaches. Reaction paths are investigated for five prototypes involving radical-radical hydrogen abstraction: H + BeH → H 2 + Be, H + NH 2 → H 2 + NH, CH 3 + C 2 H 5 → CH 4 + C 2 H 4 , H + C2H 5 → H 2 + C 2 H 4 , and H + HCO → H 2 + CO. Full configuration interaction (FCI) benchmark computations for the H + BeH, H + NH 2 , and H + HCO reactions prove that Mk-MRCCSD(T) provides superior accuracy for the interaction energies in the entrance channel, with mean absolute errors less than 0.3 kcal mol(-1) and percentage deviations less than 10% over the fragment separations of relevance to kinetics. To facilitate combustion studies, energetics for the CH 3 + C 2 H 5 , H + C 2 H 5 , and H + HCO reactions were computed at each level of theory with correlation-consistent basis sets (cc-pVXZ, X = T, Q 5) and extrapolated to the complete basis set (CBS) limit. These CBS energies were coupled with CASPT2 projected vibrational frequencies along a minimum energy path to obtain rate constants for these three reactions. The rigorous Mk-MRCCSD(T)/CBS results demonstrate unequivocally that these three reactions proceed with no barrier in the entrance channel, contrary to some earlier predictions. Mk-MRCCSD(T) also reveals that the economical CASPT2 method performs well for large interfragment separations but may deteriorate substantially at shorter distances.

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

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗
DOE OSTI2023

Emergency department overcrowding and its associated factors at HARME medical emergency center in Eastern Ethiopia

Introduction: Emergency department (ED) overcrowding has become a significant concern as it can lead to compromised patient care in emergency settings. Various tools have been used to evaluate overcrowding in ED. However, there is a lack of data regarding this issue in resource-limited countries, including Ethiopia. This study aimed to validate NEDOCS, assess level of ED overcrowding and identify associated factors at HARME Medical Emergency Center, located in Hiwot Fana Comprehensive Specialized Hospital, Harar, Ethiopia. Methods: A cross-sectional study was conducted at the HARME Medical Emergency Center, Hiwot Fana Comprehensive Specialized Hospital, involving a total of 899 patients during 120 sampling intervals. The area under the receiver operating characteristic curves (AUC) was calculated to evaluate the agreement between objective and subjective assessments of ED overcrowding. A multivariable logistic regression analysis was employed to identify factors associated with ED overcrowding and statistically significant association was declared using 95% confidence level and a p-value < 0.05. Results: The interrater agreement showed a strong correlation with a Cohen's kappa (κ) of 0.80. The National Emergency Department Overcrowding Study Score demonstrated a strong association with subjective assessments from residents and case team nurses, with an AUC of 0.81 and 0.79, respectively. According to residents' perceptions, ED were considered overcrowded 65.8% of the time. Factors significantly associated with ED overcrowding included waiting time for triage (AOR: 2.24; 95% CI: 1.54–3.27), working time (AOR: 2.23; 95% CI: 1.52–3.26), length of stay (AOR: 2.40; 95% CI: 1.27–4.54), saturation level (AOR: 2.35; 95% CI: 1.31–4.20), chronic illness (AOR: 2.19; 95% CI: 1.37–3.53), and abnormal pulse rate (AOR: 1.52; 95% CI: 1.06–2.16). Conclusion: The study revealed that ED were overcrowded approximately two-thirds of the time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Fundamental limitations of high contrast imaging set by small sample statistics

In this paper, we review the impact of small sample statistics on detection thresholds and corresponding confidence levels (CLs) in high-contrast imaging at small angles. When looking close to the star, the number of resolution elements decreases rapidly toward small angles. This reduction of the number of degrees of freedom dramatically affects CLs and false alarm probabilities. Naively using the same ideal hypothesis and methods as for larger separations, which are well understood and commonly assume Gaussian noise, can yield up to one order of magnitude error in contrast estimations at fixed CL. The statistical penalty exponentially increases toward very small inner working angles. Even at 5-10 resolution elements from the star, false alarm probabilities can be significantly higher than expected. Here we present a rigorous statistical analysis that ensures robustness of the CL, but also imposes a substantial limitation on corresponding achievable detection limits (thus contrast) at small angles. This unavoidable fundamental statistical effect has a significant impact on current coronagraphic and future high-contrast imagers. Finally, the paper concludes with practical recommendations to account for small number statistics when computing the sensitivity to companions at small angles and when exploiting the results of direct imaging planet surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantifying electron cyclotron power deposition broadening in DIII-D and the potential consequences for the ITER EC system

Abstract The injection of electron cyclotron (EC) waves fulfills a number of important tasks in nuclear fusion devices for which detailed knowledge of the spatial power deposition profile is critical. This deposition profile is commonly determined using forward models such as beam or ray tracing. Recent numerical and experimental studies have shown that small-angle scattering of the EC beam as it passes through the turbulent plasma edge can cause significant broadening of the effective deposition profile, leading to considerable underestimation of the deposition width by forward methods. However, traditional inverse methods to determine the deposition profile from measurements overestimate the deposition profile width due to transport broadening. In this work, we implement three novel methods to resolve the EC power deposition profile from measurements that counteract transport broadening by simultaneously resolving transport and power deposition. We validate their assumptions and compare the results from these methods to the traditional break-in-slope method as well as to the TORAY ray-tracing code in a set of DIII-D discharges spanning five different confinement modes. We show that the four different inverse methods, novel and established, paint a consistent picture of deposition broadening. Specifically, we show that the measured power deposition profile is between 1.6 and 3.6 times wider than the TORAY profiles. Moreover, we show the considerable consequences that this level of broadening can have for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Search for the 𝐾 𝐿 → 𝜋 0 ⁢$𝜈⁢\bar{𝜈}$ Decay at the J-PARC KOTO Experiment

We performed a search for the 𝐾 𝐿 → 𝜋 0 ⁢$𝜈⁢\bar{𝜈}$ decay using the data taken in 2021 at the J-PARC KOTO experiment. With newly installed counters and new analysis method, the expected background was suppressed to 0.252 ± 0.055 stat ⁢ $^{+0.052}_{{−0.067^{syst}}}$. With a single event sensitivity of (9.33 ± 0.0⁢6 stat ±0.8⁢4 syst ) × 10 −10 , no events were observed in the signal region. An upper limit on the branching fraction for the decay was set to be 2.2 ×10 −9 at the 90% confidence level (C.L.), which improved the previous upper limit from KOTO by a factor of 1.4. With the same data, a search for 𝐾 𝐿 → 𝜋 0 ⁢𝑋 0 was also performed, where 𝑋 0 is an invisible boson with a mass ranging from 1 to 260 MeV/𝑐 2 . For 𝑋 0 with a mass of 135 MeV/𝑐 2 , an upper limit on the branching fraction of 𝐾 𝐿 → 𝜋 0 ⁢𝑋 0 was set to be 1.6 ×10 −9 at the 90% C.L.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Data-Driven Distribution System Load Modeling for Quasi-Static Time-Series Simulation

This paper presents a data-driven distribution system load modeling methodology targeting quasi-static time-series (QSTS) simulation. The proposed methodology is appropriate for modeling down to the level of the customer transformer, and it has three main features: 1) both load pattern diversity and intra-second load variability are considered, 2) the load profiles can be populated for multiple nodes on a circuit in such a way that the diversity factor of the feeder can be defined and tuned, and 3) the load aggregation method can be used to populate the profiles for different nodes at various load aggregation levels. Furthermore, as the foundation of the modeling methodology, variability and diversity libraries have been established based on high-resolution load data collected on customer transformers from real utility feeders. The proposed modeling methodology has been used to build load data sets for both the IEEE 123-bus feeder model and a realistic utility feeder model. The QSTS simulation results on the two evaluation feeders have demonstrated that the load data sets established from the proposed modeling methodology can effectively capture the load impact on feeder operations. For the realistic utility feeder, the effectiveness of the proposed methodology has also been validated by comparing the voltage characteristics of the feeder with modeled loads and the voltage characteristics of realistic voltage data from the same feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

radkit v1.2

The radkit software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations. The radkit libraries have associated Robot Operating System packages for use in real-time and robotic systems.

Joshi, Tenzing↗
DOE OSTI2026

radkit base v1.6

The radkit (base) software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices, cameras, as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations.

Salathe, Marco [Lawrence Berkeley National Laborat↗
DOE OSTI2023

Predicting Postoperative Injury and Military Discharge Status After Knee Surgery in the US Army

Background: Researchers have assessed postoperative injury or disability predictors in the military setting but typically focused on 1 type of surgical procedure at a time, used relatively small sample sizes, or investigated mixed cohorts with civilian populations. Purpose: To identify the relationship between baseline variables and injury incidence or military discharge status in US Army soldiers after knee surgery. Study Design: Case-control study; Level of evidence, 3. Methods: Data were obtained from a repository containing personnel, performance, and medical records for all active-duty US Army soldiers. Multivariate logistic regressions were used to estimate the effects of numerous variables on postoperative injury or on medical discharge. Variable selection and model validation were conducted using the k-fold method. Results: A total of 7567 soldiers underwent knee surgery between 2017 and 2019. Meniscal procedures were the most common type of surgery (39%), and approximately 71% of the cohort had a postoperative injury. Significant predictors for sustaining a postoperative injury included having a previous nonknee injury (odds ratio [OR], 1.5), female sex (OR, 1.3), and Black race (OR, 1.2). Within 4 years after surgery, 17% of soldiers were discharged from the military because of knee-related disability. Significant predictors for discharge from duty included enlisted rank (OR, 2.3), recent fitness test failure (OR, 1.9), number of previous knee surgeries (OR, 1.7), and having a previous nonknee injury (OR, 1.6). Conclusion: After knee surgery, nearly three-fourths of the soldiers in this cohort sustained a postoperative injury and almost one-fifth of soldiers were medically discharged from the military within 4 years. This study identified variables that indicate statistically increased risk for these postoperative outcomes and highlighted potentially modifiable factors.

Orthopedics↗
DOE OSTI2015

Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-­L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-­bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-­4 weeks of an FTE split amongst two staff scientists and one post-­doc. The DEM simulations emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-­particles square by 10-­particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Sci-Thur AM: YIS – 08: Automated Imaging Quality Assurance for Image-Guided Small Animal Irradiators

Purpose: To develop quality assurance (QA) standards and tolerance levels for image quality of small animal irradiators. Methods: A fully automated in-house QA software for image analysis of a commercial microCT phantom was created. Quantitative analyses of CT linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, modulation transfer function (MTF), and CT number evaluation was performed. Phantom microCT scans from seven institutions acquired with varying parameters (kVp, mA, time, voxel size, and frame rate) and five irradiator units (Xstrahl SARRP, PXI X-RAD 225Cx, PXI X-RAD SmART, GE explore CT/RT 140, and GE Explore CT 120) were analyzed. Multi-institutional data sets were compared using our in-house software to establish pass/fail criteria for each QA test. Results: CT linearity (R2>0.996) was excellent at all but Institution 2. Acceptable SNR (>35) and noise levels (<55HU) were obtained at four of the seven institutions, where failing scans were acquired with less than 120mAs. Acceptable MTF (>1.5 lp/mm for MTF=0.2) was obtained at all but Institution 6 due to the largest scan voxel size (0.35mm). The geometric accuracy passed (<1.5%) at five of the seven institutions. Conclusion: Our QA software can be used to rapidly perform quantitative imaging QA for small animal irradiators, accumulate results over time, and display possible changes in imaging functionality from its original performance and/or from the recommended tolerance levels. This tool will aid researchers in maintaining high image quality, enabling precise conformal dose delivery to small animals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

What Makes You Hold on to That Old Car? Joint Insights From Machine Learning and Multinomial Logit on Vehicle-Level Transaction Decisions

What makes you hold on to that old car? While the vast majority of household vehicles are still powered by conventional internal combustion engines, the progress of adopting emerging vehicle technologies will critically depend on how soon the existing vehicles are transacted out of the household fleet. Leveraging a nationally representative longitudinal data set, the Panel Study of Income Dynamics, this study examines how household decisions to dispose of or replace a given vehicle are: 1) influenced by the vehicle’s attributes, 2) mediated by households’ concurrent socio-demographic and economic attributes, and 3) triggered by key life cycle events. Coupled with a newly developed machine learning interpretation tool, TreeExplainer, we demonstrate an innovative use of machine learning models to augment traditional logit modeling to both generate behavioral insights and improve model performance. We find the two gradient-boosting-based methods, CatBoost and LightGBM, are the best performing machine learning models for this problem. The multinomial logistic model can achieve similar performance levels after its model specification is informed by TreeExplainer. Both machine learning and multinomial logit models suggest that while older vehicles are more likely to be disposed of or replaced than newer ones, such probability decreases as the vehicles serve the family longer. Pickup trucks and sport utility vehicles are less likely to be disposed of or replaced than cars, and leased vehicles are more likely to be transacted than owned vehicles. We find that married families, families with higher education levels, homeowners, and older families tend to keep their vehicles longer. Life events such as childbirth, residential relocation, and change of household composition and income are found to increase vehicle disposal and/or replacement. We provide additional insights on the timing of vehicle replacement or disposal, in particular, the presence of children and childbirth events are more strongly associated with vehicle replacement among younger parents.

33 ADVANCED PROPULSION SYSTEMS↗