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DOE OSTI2016

Developing Detectors for Scintillation Light in Liquid Argon for DUNE

The Deep Underground Neutrino experiment will conduct a broad program of physics research by studying a beam of neutrinos from Fermilab, atmospheric neutrinos, neutrinos from potential supernovae, and potential nucleon decay events. In pursuit of these studies, the experiment will deploy four 10kt fiducial mass liquid argon time projection chambers underground in Lead, South Dakota. Liquid argon time projection chambers allow high-resolution tracking and energy measurements. A precise timing signal is needed to provide the necessary time stamp to localize events in the drift direction. As liquid argon is a natural scintillator, a photon detection system will be deployed to provide such a signal, especially for non-beam events. In the baseline design for the single-phase time projection chamber, the detectors are contained within the anode plane assemblies. The design of two prototypes utilizing wavelength shifters and light guides are presented, and aspects of the research and development program are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Partner Baseline Assessment Guide: Clean Energy for Low Income Communities

The U.S. Department of Energy Better Buildings Clean Energy for Low Income Communities Accelerator aims to lower energy bills in low to moderate income communities through expanded installation of energy efficiency and distributed renewables. Upon joining the Accelerator, partners committed to developing Action Plans after a year. As shown in the diagram below, baselining is a useful approach to informing your planning efforts, and should involve input from a broad range of stakeholders. The following guide was developed by DOE to assist partners with baselining, and identifying needs and gaps to address in action plans.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Neutrino oscillation prospects with a dual-baseline beam from BNL to SNOLAB and SURF

The Electron-Ion Collider (EIC) is a next-generation accelerator primarily designed to study the internal structure of nucleons through high-precision electron-hadron collisions. In this work, we explore the feasibility of employing a 1 MW fraction of the EIC proton beam to generate a high-intensity GeV-scale neutrino beam for long-baseline oscillation studies. We have simulated proton-target interactions and optimize the resulting neutrino fluxes for water-based liquid scintillator (WbLS) detectors located at distinct baselines of 900 km and at 2900 km. Oscillation analyses performed with GLoBES show that extended baselines allow access to multiple oscillation maxima, significantly enhancing sensitivity to leptonic CP violation. The study also examines the interplay between matter effects and the intrinsic CP violating phase in shaping observable asymmetries. We note that simplified systematics and no backgrounds are used in this analysis to establish the baseline physics potential. These results suggest that the EIC proton beam could provide a novel and complementary source for precision neutrino physics, extending the scientific reach of the EIC program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Modeling efficient and equitable distribution of COVID-19 vaccines

Producing and distributing COVID-19 vaccine during the pandemic is a major logistical challenge requiring careful planning and efficient execution. This report presents information on logistical, policy and technical issues relevant to rapidly fielding a COVID-19 vaccination program. For this study we (a) conducted literature review and subject matter expert elicitation to understand current vaccine manufacturing and distribution capabilities and vaccine allocation strategies, (b) designed a baseline vaccine distribution strategy and modeling strategy to provide insight into the potential for targeted distribution of limited initial vaccine supplies, and (c) developed parametric interfaces to enable vaccine distribution scenarios to be analyzed in depth with Sandias Adaptive Recovery Model that will allow us evaluate the additional sub- populations and alternative distribution scenarios from a public health benefit and associated economic disruption Principal issues, challenges, and complexities that complicate COVID-19 vaccine delivery identified in our literature and subject matter expert investigation include these items: The United States has not mounted an urgent nationwide vaccination campaign in recent history. The existing global manufacturing and distribution infrastructure are not able to produce enough vaccine for the population immediately. Vaccines, once available will be scarce resources. Prioritization for vaccine allocation will be built on existing distribution networks. Vaccine distribution may not have a universal impact on disease transmission and morbidity because of scarcity, priority population demographics, and underlying disease transmission rates. Considerations for designing a vaccine distribution strategy are discussed. A baseline distribution strategy is designed and tested using the Adaptive Recovery Model, which couples a deterministic compartmental epidemiological model and a stochastic network model. We show the impact of this vaccine distribution strategy on hospitalizations, mortality, and contact tracing requirements. This model can be used to quantitatively evaluate alternative distribution scenarios, guiding policy decisions as vaccine candidates are narrowed down.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

FY2018 Discovery Through Situational Awareness: Anomalies, Oscillations, and Classification

This technical report is a summary of work performed under the DOE GMLC program under the task titled “Discovery through Situational Awareness”. The focus of this work was to apply big data, statistical techniques to PMU data to do the following: 1) baseline PMU data and find anomalies with a focus on phase angle pairs, 2) identify the frequencies of dominant modal oscillations between different parts of a power system, and 3) identify and classify frequency events in PMU data. This work was performed on PMU data from the Western Interconnect. Many of these algorithms will be applied to wide area phase angle pair data on the Eastern Interconnect in a tool called ESAMS (Eastern Interconnect Situational Awareness Monitoring System). ESAMS was built by EPG (Electric Power Group) and PNNL and is currently being installed on the Eastern Interconnect. The results discussed in this report were made from 14 PMUs from data ranging from Oct 2016 to May 2018. The PMU data were measured 60 times each second. Fourteen phase angle pairs were included, with reactive and active power being calculated at 14 sites. All results have been de-identified for this report. The methodologies applied in the ESAMS tool are described in Section 2. A baseline of PMU data is created using the last 120 days of data. This baseline describes typical behavior as understood from the data. The baseline is then applied to the next day’s data and anomalies from that baseline are identified. Plots are created to help describe what is anomalous during that specific moment in time. These algorithms are currently being installed on the Eastern Interconnect. FY19 work will include discussing the results and findings from the ESAMS tool. A new method of identifying the frequencies of dominant modal oscillations between different parts of a power system is described in Section 3. A list of 199 frequency events provided by Bonneville Power Administration were used to create algorithms to detect frequency events and to create classification rules that can be used to identify future frequency events. Section 4 discusses the results the performance of 7 different event detection, clustering-based methods. Accuracy percentages ranged from 93.59% to 99.16%, with most methods being very fast. GBM (Gradient Boosting Machine) performed well and quickly. These 7 different methods were also tested to determine how well each built classification rules on training data and then applied those rules to identify future frequency events. Accuracy percentages ranged from 89.09% to 99.9%, with all methods performing quickly. GLM (General Linear Model) was viewed as the top performer when considering accuracy and processing time. Because the list of events consisted of 80% of them as active power events and only 20% as faults, all methods struggled to identify events as faults. Small faults were especially difficult to identify. A separate algorithm was created to help with this. Additional work will be done in FY19 on event detection using more data and more events and refinements to the methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Statistical analysis of pulsed-neutron well logs in monitoring injected carbon dioxide

Pulsed-neutron well logs (PNLs) were acquired to monitor CO 2 storage associated with enhanced oil recovery. This work quantifies the precision of repeat PNLs using data from four wells and 15 repeat PNLs. Root-mean-square (RMS) precision for the repeat PNLs was less than 3%, indicating good agreement between the baseline and repeat PNLs. Evaluations of scaled relative difference (Scaled-D) showed variation in precision among individual wells and formations. Analysis of false-positive rates (FPRs) across the entire data set showed that a Scaled-D threshold in sandstone formations of approximately ±8% resulted in a 1% FPR. These Scaled-D precision thresholds were used to estimate the value of CO 2 saturation able to be confidently distinguished from baseline. The detection limit for CO 2 is lowest for high-porosity formations filled with saline water and is highest for low-porosity formations filled with fresh water. Thus, detection of vertical out-of-zone CO 2 migration using repeat PNLs is a function of instrument precision, petrophysical properties, and hydrology, all of which must be taken into account as part of the monitoring program. Here, the results of this work provide insight into how PNLs may be included within monitoring plans to detect vertical out-of-zone CO 2 migration along a wellbore or instances of wellbore failure and provide a quantitative basis for establishing detection limits of repeat PNLs to distinguish change from baseline conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Ultra Barrier Topsheet Film for Flexible Photovoltaics with 3M Company

In this DOE sponsored program, 3M achieved the critical UBT features to enable durable flexible high efficiency modules to be produced by a range of customers who have now certified the 3M UBT and are actively developing said flexible modules. The specific objectives and accomplishments of the work under this program were; Scale-up the current Generation-1 UBT from 12” width, as made on 3M’s pilot line, to 1+meter width full-scale manufacturing, while maintaining baseline performance metrics (see table below); This objective was fully met; Validate service life of Generation-1 UBT for the 25+ year lifetime demanded by the photovoltaic market; Aggressive testing revealed potential failure modes in the Gen 1 UBT. Deficiencies were identified and corrective action taken in the Gen 2 UBT; Develop a Generation-2 UBT on the pilot line, targeting improved performance relative to baseline, including higher %T (percent transmission), lower water vapor transmission rate (WVTR) with targets based on what the technology needs for 25 year lifetime, proven lifetime of 25 years in solar module construction in the field, and lower cost; Testing of UBT Gen 2 under a wide range of conditions presented in this report failed to reveal any failure mode. Therefore UBT Gen 2 is known to be highly durable. 3M will continue to test towards statistically validating a 25 year lifetime under 3M funding; Transfer Generation-2 UBT from the pilot line to the full-scale manufacturing line within three years; and This objective was fully met.

14 SOLAR ENERGY↗

DOE OSTI2019

Hardware Evaluation Outreach: Application development Challenges Now and for the Exascale Era

The intent of this document is to assist the programmer in understanding details of contemporary and Exascale hardware system design and how these designs provide opportunities and place constraints on next-generation simulation software design. We attempt to clarify hardware organization and component details for our most current and Exascale systems to help program developers understand how software needs to change in order to take best advantage of the performance available. Exascale success is specifically defined for ECP as a 50x improvement over baseline in the aggregate "capability volume" on several KPP axes, of which raw floating point performance is only one, but also includes characteristics such as problem size, system memory size, node memory size, power, and efficiency. This multi-axis approach is particularly important to understand in the context of delivered improvements in real applications, since, for instance, the floating point computation may comprise less than 10% of the actual computational work required. Given the Exascale requirements and the constraints these requirements put on the performance expectations of fundamental system components, the programmer will be forced to re-think several application implementation details in order to achieve exaflop performance on these systems. The remainder of this document aims to present more detail on Exascale era system hardware and the specific areas that the programmer should address to extract performance from these systems. We attempt to give the programmer guidance at both a high- and low-level, providing some abstract suggestions on how to refactor codes given the expected system architectures and some low-level recommendations on how to implement these modifications. We also include a section on training resources that are helpful for both programmers that are just beginning to understand code modifications for contemporary and Exascale systems and for those that have done some refactoring and are now trying to extract maximal application performance from these systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Corrosion Protection and Dissimilar Material Joining for Next Generation Lightweight Vehicles

The Arconic Technology Center working with Honda R&D Americas, LLC and the Ohio State University evaluated the corrosion performance of several multi-material conditions and demonstrated the production worthiness of the Resistance Spot Riveting (RSR™) process. RSR is a new technology being developed by Howmet Fastening Systems (formerly Arconic, Inc.) that employs a fastener that is installed using conventional resistance spot welding equipment to produce multi-material joints. The goal of the 3-year project was to demonstrate the use of RSR to join aluminum to steel and aluminum to carbon fiber composites on a prototype scale. Deployment of this technology would help the automotive industry achieve an additional 10 to 20% weight reduction over high strength steels. These weight-savings to the body in white generally translates to 2.5-5.0% of overall vehicle curb weight. The resulting total weight-savings could provide a 1.5% to 3.0% total improvement in fuel efficiency for vehicles that incorporate RSR for multi-material joining. The RSR technology addresses several production barriers to achieving DOE’s fuel efficiency targets including eliminating the need of additional capital for new joining technologies and the flexibility to process conventional steel and multi-material structures with the same equipment. Additionally, the trend towards ultra-high strength steels limits the availability of conventional joining technologies that can effectively process these multi-material combinations. In order to accomplish these goals, the following program milestones were completed by the team: 1) Developed RSR process parameters, producing multi-material joints for mechanical testing and corrosion assessments. 2) Conducted corrosion evaluation of RSR and baseline joints assembled between automotive type aluminum alloys, steels, and carbon fiber using several corrosion mitigation strategies. 3) Developed a production ready feed system and integrate into a robotic resistance spot welding station to simulate automotive production conditions. 4) Produced demonstration assemblies for testing and evaluation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Installation and Demonstration of CNC Machining for Mechanical Test Specimens in the IFEL Hot Cell

This report documents the installation and demonstration of computer numerical control (CNC) machining capabilities in the Irradiated Fuels Examination Laboratory hot cell facility at Oak Ridge National Laboratory (ORNL). A modified Tormach PCNC 440 mill was integrated into the hot cell with custom fixturing, fines management, and manipulator-compatible interfaces to enable the fabrication of axial tension test (ATT) and ring tension test (RTT) specimens from irradiated cladding. The first irradiated specimens machined included ATT and RTT geometries harvested from the high-burnup 6XV fuel rod. Dimensional inspections confirmed that machined specimens met the ±0.025 mm tolerance envelope established in prior development; deviations were consistent with expected measurement scatter and inherent specimen variability, such as wall thickness gradients and eccentricity. Comparisons with out-of-cell metrology confirmed that in-cell machining performance aligns with baseline scatter observed under ideal conditions. This work establishes reproducible, end-to-end specimen preparation at ORNL, directly supporting the US Department of Energy’s Accident-Tolerant Fuel program by enabling reliable, traceable mechanical testing of irradiated cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Fuel Fabrication Capability Research and Development Plan

The purpose of this document is to provide a comprehensive review of the mission of the Fuel Fabrication Capability (FFC) within the Global Threat Reduction Initiative Convert Program, along with research and development (R&D) needs that have been identified as necessary to ensuring mission success. The design and fabrication of successful nuclear fuels must be closely linked endeavors. Therefore, the overriding motivation behind the FFC R&D program described in this plan is to foster closer integration between fuel design and fabrication to reduce programmatic risk. These motivating factors are all interrelated, and progress addressing one will aid understanding of the others. The FFC R&D needs fall into two principal categories, 1) baseline process optimization, to refine the existing fabrication technologies, and 2) manufacturing process alternatives, to evaluate new fabrication technologies that could provide improvements in quality, repeatability, material utilization, or cost. The FFC R&D Plan examines efforts currently under way in regard to coupon, foil, plate, and fuel element manufacturing, and provides recommendations for a number of R&D topics that are of high priority but not currently funded (i.e., knowledge gaps). The plan ties all FFC R&D efforts into a unified vision that supports the overall Convert Program schedule in general, and the fabrication schedule leading up to the MP-1 and FSP-1 irradiation experiments specifically. The fabrication technology decision gates and down-selection logic and schedules are tied to the schedule for fabricating the MP-1 fuel plates, which will provide the necessary data to make a final fuel fabrication process down-selection. Because of the short turnaround between MP-1 and the follow-on FSP-1 and MP-2 experiments, the suite of specimen types that will be available for MP-1 will be the same as those available for FSP-1 and MP-2. Therefore, the only opportunity to explore parameter space and alternative processing is between now and 2016 when the candidate processes are down-selected in preparation for the MP-1, FSP-1, and MP-2 plate manufacturing campaigns. A number of key risks identified by the FFC are discussed in this plan, with recommended mitigating actions for those activities within FFC, and identification of risks that are impacted by activities in other areas of the Convert Program. The R&D Plan does not include discussion of FFC initiatives related to production-scale manufacturing of fuel (e.g., establishment of the Pilot Line Production Facility), rather, the goal of this plan is to document the R&D activities needed ultimately to enable high-quality and cost-effective production of the fuel by the commercial fuel fabricator. The intent is for this R&D Plan to be a living document that will be reviewed and updated on a regular basis (e.g., annually) to ensure that FFC R&D activities remain properly aligned to the needs of the Convert Program. This version of the R&D Plan represents the first annual review and revision.

Convert Program↗

DOE OSTI2016

OpenStudio: A Platform for Ex Ante Incentive Programs

Many utilities operate programs that provide ex ante (up front) incentives for building energy conservation measures (ECMs). A typical incentive program covers two kinds of ECMs. ECMs that deliver similar savings in different contexts are associated with pre-calculated 'deemed' savings values. ECMs that deliver different savings in different contexts are evaluated on a 'custom' per-project basis. Incentive programs often operate at less than peak efficiency because both deemed ECMs and custom projects have lengthy and effort-intensive review processes--deemed ECMs to gain confidence that they are sufficiently context insensitive, custom projects to ensure that savings are claimed appropriately. DOE's OpenStudio platform can be used to automate ex ante processes and help utilities operate programs more efficiently, consistently, and transparently, resulting in greater project throughput and energy savings. A key concept of the platform is the OpenStudio Measure, a script that queries and transforms building energy models. Measures can be simple or surgical, e.g., applying different transformations based on space-type, orientation, etc. Measures represent ECMs explicitly and are easier to review than ECMs that are represented implicitly as the difference between a with-ECM and without-ECM models. Measures can be automatically applied to large numbers of prototype models--and instantiated from uncertainty distributions--facilitating the large scale analysis required to develop deemed savings values. For custom projects, Measures can also be used to calibrate existing building models, to automatically create code baseline models, and to perform quality assurance screening.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by the Circle Economy Foundation states that the circularity score for the global economy is declining. The US Environmental Protection Agency (EPA) tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste was destined for landfills. EPA estimates that US industry is responsible for 2.7 Gt of solid nonhazardous waste annually in the US mostly linear economy model. The circular economy framework aims to decouple economic value generation from the extraction of virgin materials from nature. The linear model of material extraction and disposal at the end of life is highly unsustainable. Manufacturing companies are adopting ambitious waste reduction targets to achieve sustainability. Through the Better Plants program, US DOE has established the Waste Reduction Network, which offers technical assistance to partners to achieve their ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is unstandardized metrics for quantifying waste performance that may not be well suited to demonstrate progress. This paper studies traditional methods used to measure waste performance and highlights advantages, disadvantages, and limitations of each method. It also examines the suitability of applying the methods in different manufacturing circumstances. Finally, the paper presents a case study of a large manufacturer that faced inconsistencies in its tracked measurement metric. A solution was proposed and implemented to alter the methodology to enable more accurate waste performance tracking against a baseline.

circular economy↗

DOE OSTI2014

Optimal Location of Radiation Therapy Centers With Respect to Geographic Access

Purpose: To develop a framework with which to evaluate locations of radiation therapy (RT) centers in a region based on geographic access. Methods and Materials: Patient records were obtained for all external beam radiation therapy started in 2011 for the province of British Columbia, Canada. Two metrics of geographic access were defined. The primary analysis was percentage of patients (coverage) within a 90-minute drive from an RT center (C90), and the secondary analysis was the average drive time (ADT) to an RT center. An integer programming model was developed to determine optimal center locations, catchment areas, and capacity required under different scenarios. Results: Records consisted of 11,096 courses of radiation corresponding to 161,616 fractions. Baseline geographic access was estimated at 102.5 minutes ADT (each way, per fraction) and 75.9% C90. Adding 2 and 3 new centers increased C90 to 88% and 92%, respectively, and decreased ADT by between 43% and 61%, respectively. A scenario in which RT was provided in every potential location that could support at least 1 fully utilized linear accelerator resulted in 35.3 minutes' ADT and 93.6% C90. Conclusions: The proposed framework and model provide a data-driven means to quantitatively evaluate alternative configurations of a regional RT system. Results suggest that the choice of location for future centers can significantly improve geographic access to RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

Data Release Report for Source Physics Experiments 2 and 3 (SPE-2 and SPE-3) Nevada National Security Site

The second Source Physics Experiment shot (SPE-2) was conducted in Nevada on October 25, 2011, at 1900:00.011623 Greenwich Mean Time (GMT). The explosive source was 997 kilograms (kg) trinitrotoluene (TNT) equivalent of sensitized heavy ammonium fuel oil (SHANFO) detonated at a depth of 45.7 meters (m). The third Source Physics Experiment shot (SPE-3) was conducted in Nevada on July 24, 2012, at 1800:00.44835 GMT. The explosive source was 905 kg TNT equivalent of SHANFO detonated at a depth of 45.8 m. Both shots were recorded by an extensive set of instrumentation that includes sensors both at near-field (less than 100 m) and far-field (100 m or greater) distances. The near-field instruments consisted of three-component accelerometers deployed in boreholes at 15, 46, and 55 m depths around the shot and a set of single-component vertical accelerometers on the surface. The far-field network was composed of a variety of seismic and acoustic sensors, including short-period geophones, broadband seismometers, three-component accelerometers, and rotational seismometers at distances of 100 m to 25 kilometers. This report coincides with the release of these data for analysts and organizations that are not participants in this program. This report describes the second and third Source Physics Experiment shots and the various types of near-field and farfield data that are available.This revised document includes reports on baseline shift corrections for the SPE-2 and SPE-3 shots that were missing from the original January 2015 version.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Sample Collection Metadata for Soil Cores from the East River Watershed, Colorado collected in 2017

This data package contains sample collection metadata for soil cores from the East River Watershed in Colorado used in biogeochemical analyses by the Watershed Function SFA. Soil cores were collected seasonally during autumn, winter, snowmelt, and spring at a predominately montane meadow, high altitude field site. Information provided for each soil core sample assigned an International Geo Sample Number (IGSN) includes: sample name, IGSN, material, description, collection method, core depth, location, field program, collectors, and date. The full list of 53 IGSN's is listed in the Methods section. There is also a complete core sample list and metadata for the set of baseline data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Baseline Face Detection, Head Pose Estimation, and Coarse Direction Detection for Facial Data in the SHRP2 Naturalistic Driving Study

Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume, and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.

Paone, Jeffrey R↗