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Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Abstract. Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25∘×0.25∘) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

54 ENVIRONMENTAL SCIENCES↗

ROOT RNTuple and EOS: The Next Generation of Event Data I/O

For several years, the ROOT team is developing the new RNTuple I/O subsystem in preparation of the next generation of collider experiments. Both HL-LHC and DUNE are expected to start data taking by the end of this decade. They pose unprecedented challenges to event data I/O in terms of data rates, event sizes, and event complexity. At the same time, the I/O landscape is becoming more diverse. HPC cluster file systems and object stores, NVMe disk cache layers in analysis facilities, and S3 storage on cloud resources are mixing with traditional XRootD-managed spinning disk pools.The ROOT team will finalize a first production version of the RNTuple binary format by the end of 2024. After this point, ROOT will provide backward compatibility for RNTuple data. This contribution provides an overview of the RNTuple feature set, the related R&D activities and the long-term vision for RNTuple. We report on performance, interface design, tooling, robustness, integration with experiment frameworks, and validation results, as well as recent R&D on parallel reading and writing and exploitation of modern hardware and storage systems. We will give an outlook on possible future features after a first production release.Collaboratively, the IT and EP departments at CERN have launched a formal project within the Research and Computing sector to evaluate the novel data format for physics analysis data utilized in LHC experiments and other fields. This part of the project focuses on validating the scalability of the EOS storage backend during the transition from the over 25 years old TTree production format to the newly developed RNTuple format, using both replicated and erasure-coded storage profiles.

Blomer, Jakob [CERN]↗

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗

1990 St. Louis Region Travel Survey

The 1990 St. Louis Region Travel Survey was performed in the fall of 1990 for the St. Louis region. The study was done for the East-West Gateway Coordinating Council by Barton-Aschman Associates, Inc., with assistance from NSI Research Group. The area surveyed included the city of St. Louis, St. Louis County, and parts of Jefferson County, Madison County, St. Clair County, Monroe County, and St. Charles County. The survey was used primarily for the calibration of trip production models. Other uses will include the calibration of trip attraction models and trip distribu¬tion models. The total number of completed, useable household samples for the survey area totaled 1,446.

1Hz data↗

Decarbonizing the Building Sector: A Human-Centered Study Focused on Small/Light Commercial Building Energy Equity

Decarbonization of the building sector is no small feat; buildings account for 40% of primary energy consumption, and fossil-fuel combustion in buildings leads to roughly 30% of total greenhouse gas emissions. Energy efficiency, electrification and smart technologies are fundamental strategies to reduce consumption and shift away from fossil-fuel use in buildings. This energy transition carries significant societal risks unless the shift is carried out with equity and justice as a top priority. Low-income, vulnerable and communities of color have higher energy burdens compared to affluent populations. Furthermore, systemic racism and historic exclusionary policies have resulted in increased risks (environmental, climatic, economic, and social) to low-income and communities of color, and underserved communities often do not have financial resources for, or access to, advanced building technologies. The U.S. Department of Energy is funding research to characterize and develop solutions to the challenges of equity and justice that complicate the ability of communities to contribute to goals for decarbonization. Our project has a specific focus on small commercial buildings and the businesses that occupy them. Significantly less is known about the burdens and risks these businesses experience or the challenges they face in pursuing decarbonization, or how those are affected by income and race, in comparison to research on energy equity and justice for diverse households. The project team includes the Pacific Northwest National Laboratory, Arizona State University and Clark Atlanta University. Researchers are conducting semi-structured interviews with small business owners in underserved communities in Phoenix and Atlanta, followed by a survey distributed to the larger community to learn more about the equity and justice issues that communities with different racial, economic, and cultural backgrounds face. Results will help inform an actionable and replicable framework for engaging small commercial building owners/operators to catalyze the reduction of energy burdens and increase equity.

Antonopoulos, Chrissi A.↗

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

Glycolate Analysis in Tank 22: Developing and Testing Analytical Methods for the Savannah River Site Liquid Waste System

Researchers developed and tested a range of techniques to support a low mg/L Limit of Quantitation (LOQ) of glycolate in radioactive Tank 22 waste solution by Ion Chromatography (IC) and by proton NMR. For the IC method, Dionex OnGuard II cartridges were tested as a means of removing alkali earth and transition metals that can interfere during ion chromatography applications especially when analyzing for low-concentration, chelating analytes. Additionally, concentrations of nitrate in the raw Tank 22 sample (5,000 to 10,000 mg/L) were managed by using reasonable levels of sample dilution. The resulting IC performance quality was enhanced by improving the baseline, increasing sensitivity [Limit of Quantitation (LOQ) of 12 mg/L and Limit of Detection (LOD) of 4.0 mg/L], and resolving analytes into well-defined Gaussian peaks when using the Dionex OnGuard II H⁺ cartridges to remove matrix interferences. High concentrations of nitrate limited the performance of the IC method. To achieve an acceptable baseline, samples with high nitrate content require more dilution, resulting in higher detection limits. Tests on samples with higher concentrations of nitrate (Tank 30 and 32 supernate with approximately 150000 mg/L nitrate) suggested that IC detection limits for glycolate in these samples would be > 500 mg/L. Thus, an LOQ of 12 mg/L is not feasible by this IC method on evaporator feed samples. An alternative method of glycolate analysis, using proton nuclear magnetic resonance (H NMR), was developed by the research team. In initial tests, the H NMR technique provided reasonable quantitation of glycolate in Tank 22 conditions by direct observation of the liquid. The H NMR method may provide improved detection limits for solutions with higher nitrate concentrations. We recommend further development of this analysis for high nitrate LWS samples such as evaporator feed and evaporator drop tank content. A method for pretreatment of samples using crystalline silicotitanate (CST) was developed and tested. The objective of the pretreatment was to facilitate analysis of samples with higher levels of radioactivity. The pretreatment did not influence the glycolate concentration in solution, and the pretreatment is projected to reduce Cs 137 activity in a sample by a factor of 16,200. The double strike CST pretreatment was demonstrated and would allow milliliters of higher activity samples to be transferred from the Shielded Cells and handled in a containment unit for glycolate analysis. The various studies validated IC and H NMR methods for glycolate analysis, defined the range of applicability, and demonstrated key supporting analytical protocols. Based on the results, high quality glycolate analysis of Tank 22 is feasible down to approximately 12 mg/L, with the potential for broader applicability of the methods to other conditions in the Savannah River Site Liquid Waste System (LWS).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Energy in Modular (EMOD) Buildings Method: A Guide to Energy-Efficient Design for Industrialized Construction of Modular Buildings

Industrialized construction has immense potential to address the growing need globally to build and upgrade the building stock to be affordable, energy-efficient, and resilient. It can also help achieve the United States' goal of a 50% reduction in U.S. greenhouse gas (GHG) emissions by 2030. Despite this potential, and the ever-increasing push for electrification and decarbonization of households in the United States, industrialized construction has not yet been leveraged specifically to help address these challenges and accelerate the pathway to meet these goals. The National Renewable Energy Laboratory (NREL) aims to claim this missed opportunity by focusing on delivering affordable, grid-efficient net-zero energy (NZE) modular buildings for underserved communities to ensure an equitable transition to the future of clean energy, accelerate decarbonization of the built environment, and support the development of a high-productivity construction and energy efficiency workforce. The Energy in Modular (EMOD) method is our approach to designing, producing, and delivering affordable, net-zero energy, low-carbon, and healthier buildings at scale. The following energy efficiency strategies are part of the scope of this guide: envelope thermal control, envelope infiltration control, mechanical, electrical, and plumbing systems, smart controls, and solar plus storage. We draw synergies between design for manufacturing and assembly, process optimization, retrofit technologies, and digitization. Our goal is to influence the improvement and production of buildings to increase performance, enhance energy efficiency, and reduce GHG emissions. This guide documents the research and development efforts initiated by a set of design objectives to "modularize" a set of energy efficiency and low-carbon strategies into a housing unit while preserving and enhancing energy efficiency benefits and decarbonization pathways. This guide is intended to serve as a framework for housing developers, housing agencies, architects, energy experts, and process engineers or factory operator personnel who are critical to today's modular builder teams. This guide focuses on specific energy efficiency strategies, decarbonization pathways, and associated processes as part of NREL's research efforts. Stakeholders may substitute other means, methods, and technologies for the ones evaluated in this study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Solid State Quantum Refrigeration Superconducting, Absorption and Measurement Based (Final Technical Report)

During this DOE grant, DE-SC0017890, in place for the past six years, all proposed research was carried out and published in peer-reviewed papers, as well as other projects that emerged during the research. In that effort the research team accomplished all proposed research, as well as many closely related research projects discovered and conceived of during the grant. These works included “Efficient Quantum Measurement Engines”, a work published in Physical Review Letters, giving a theory of quantum measurement-based engines, which uses quantum measurement as a resource. These engines are designed to efficiently convert energy from the stochastic quantum measurement process into useful work. Further publications include “Experimental Realization of a Quantum Dot Energy Harvester”, a joint theory and experimental work in collaboration with the group of Charles Smith in Cambridge, UK, as well as long time theoretical collaborators, Rafael Sánchez and Björn Sothmann. This work, featured as an Editor’s Suggestion in Physical Review Letters, realized an earlier theoretical proposal of ours, whereby two resonant tunneling quantum dots are connected to a central electronic cavity that is heated by a hot energy source. We also published “Superconducting Quantum Refrigerator: Breaking and Rejoining Cooper Pairs with Magnetic Field Cycles” a work done in collaboration with experimentalist Francesco Giazotto from ENS Pisa, Italy, which also resulted in a patent. This paper, published in Phys. Rev. Applied, advanced the concept of a cyclic fridge based on the normal/superconducting phase transition together with layered materials separated by tunnel junctions. We also completed the proposed research on a heat transistor, publishing “Thermal transistor and thermometer based on Coulomb-coupled conductors”, carried out as a collaboration between my group and theorists Splettstoesser (Lund U., Sweden), Sothmann (U. Duisburg-Essen, Germany), and Sánchez (U. Autónoma de Madrid, Spain). We carried out an analysis of a quantum coupled to a quantum point contact as a sensitive thermometer and heat transistor. We found the optimal statistical estimator for the temperature and compared it with experiments on the same type of devices. We also investigated autonomous quantum absorption refrigerators using quantum dots to cool by using a very hot thermal reservoir to drive heat between two other reservoirs. In the article “Quantifying the quantum heat contribution from a driven superconducting circuit”, we demonstrated that for a driven superconducting circuit, we showed heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. In the work “Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine”, we reconsidered the autonomous thermoelectric heat engine in terms of underlying cycles. Rather than periodic behavior, the cycles were stochastic in nature. Nevertheless, by undertaking a graph theoretical analysis of the elementary transport processed, great quantitative and qualitative insight could be found. We also considered the quantum measurement process and showed that a quantum version of Maxwell’s demon could be related to the work extraction of a quantum system, closely related to arrow-of-time measures for quantum measurement, as described in our article “Thermodynamics of quantum measurement and Maxwell's demon's arrow of time”. This work was selected in Phys. Rev. A as an Editor’s Suggestion. A recent preprint titled “Cyclic Superconducting Quantum Refrigerators Using Guided Fluxon Propagation” accomplished an important piece of this grant: to propose a new kind of quantum refrigerator using the dynamics of fluxons in a type II superconductor. This invention envisioned a race-track type geometry where fluxons are confined. By applying a gradient of magnetic field together with electric current in a Corbino geometry, the circulating fluxons can actively cool a cold reservoir, realizing a new type of cyclic superconducting refrigerator. We also investigated the possibility of thermal control from different points of view. The application of quantum measurement to the system gives a new kind of control on the system of interest – we have pioneered this approach and shown that measurement can boost the thermal power of quantum engines as described in “Continuous measurement boosted adiabatic quantum thermal machines”. The ability to have heat flows on demand is an outstanding challenge, and we have provided new solutions to this problem in Thermal control across a chain of electronic nanocavities” for a chain of electron cavities using gating voltage control. The control methods using qubit/qubit coupling to create absorption fridges at their most fundamental level have also been developed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ghent Generating Station Nuclear Study: Siting Evaluation

The purpose of this initial siting evaluation is to assess the suitability of the PPL Corporation (PPL) owned land at/near the Kentucky Utilities Ghent Generating Station (GGS) for the deployment of advanced nuclear reactors and to determine if there are any exclusionary or avoidance factors associated with siting nuclear power at GGS. The formal siting process for a nuclear reactor requires a great level of time (i.e., multiple years), effort, and detail. The Electric Power Research Institute (EPRI) estimates the formal siting process could take a dedicated team between one and three years to complete. This initial siting evaluation considers several characteristics (e.g., environmental conditions, seismic concerns, footprint, water use, etc.) and highlights favorable/preferred characteristics as well as potential risks to feasibility. Potential risks were explored in greater detail to provide PPL with additional insights to support decision planning. The results indicate the strengths and weaknesses associated with the GGS site as a location for a nuclear generating station and are intended to inform PPL’s next steps. The results of this initial siting evaluation will also inform the selection of candidate nuclear technologies for the GGS site that align with PPL’s mission and business objectives.

99 GENERAL AND MISCELLANEOUS↗

MSD CoP Webinar: Accounting for distributive justice in model-based decision support

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Model-based analyses play an ever-increasing role in informing policy and decision-making. However, many large-scale societal challenges unavoidably involve questions about the fair distribution of positive and negative consequences. How are the costs of the energy transition distributed over households and businesses? How are flood risks redistributed under different flood risk management plans? How are the impacts of climate change and climate mitigation distributed over different parts of the world?These kinds of questions play an important role when deliberating public policy, and the lack, in many cases, of clear answers becomes an obstacle to decision-making. At recent COPs, for example, wicked questions about loss and damages and the phase-out versus phase-down of coal became obstacles to global climate action, illustrating the misalignment of the direction of scientific research and decision-makers' information needs. In this talk, I'll explore advances that are being made that enable analysts to start providing grounded model-based answers to questions of distributive justice, as well as argue that analysts should embrace and explicate the normative nature of their work instead of hiding behind the purported neutrality of science. Presenters: Dr. Jan Kwakkel (Delft University of Technology) Moderator(s): Rebecca Saari (MSD CoP Working Group Co-Chair; Univ. of Waterloo), Matt Sparks (Univ. of Waterloo); Sarah Fletcher (MSD CoP Working Group Co-Chair; Stanford University), Juan Moreno-Cruz (Univ. of Waterloo), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 13, 2024 from 1 PM - 2:15 PM ET

Kwakkel, Jan H.↗

Exploring the potential benefits of high-efficiency dual-fuel combustion on a heavy-duty multi-cylinder engine for SuperTruck I

In support of the Daimler SuperTruck I team’s 55% brake thermal efficiency (BTE) pathway goal, researchers at Oak Ridge National Laboratory performed an experimental investigation of the potential efficiency and emissions benefits of dual-fuel advanced combustion approaches on a modified heavy-duty 15-L Detroit™ DD15 engine. For this work, a natural gas port fuel injection system with an independent injection control for each cylinder was added to the DD15 engine. For the dual-fuel strategies investigated, 65%–90% of the total fuel energy was supplied through the added port fuel injection natural gas (NG) fueling system. The remaining fuel energy was supplied by one or more direct injections of diesel fuel using the production high pressure diesel fueling system. The production DD15 air handling system and combustion geometry were unmodified for this study. Efficiency and emissions with dual-fuel strategies including both low temperature combustion (LTC) and non-LTC approaches such as dual fuel direct-injection were investigated along with control authority over combustion phasing. Parametric studies of dual-fuel NG/diesel advanced combustion were conducted in order to experimentally investigate the potential of high-efficiency, dual-fuel combustion strategies to improve BTE in a multi-cylinder engine, understand the potential reductions in engine-out emissions, and characterize the range of combustion phasing controllability. Characterization of mode transitions from mixing-controlled diesel pilot ignition to kinetically controlled ignition is presented. Key findings from this study included a reproducible demonstration of BTE approaching 48% at up to a 13-bar brake mean effective pressure with significant reductions in engine-out NOx and soot emissions. Additional results from investigating load transients in dual-fuel mode and initial characterization of particle size distribution during dual-fuel operation are presented.

33 ADVANCED PROPULSION SYSTEMS↗

1995 OKI Household Activity and Travel Report Survey

The OKI Household Activity and Travel Report Survey 1995, conducted by Market Opinion Research, gathered household activity and travel data from 3,000 households within the OKI region (Ohio, Kentucky, and Indiana Council of Governments' service area). The region covers over 2,615 square miles and is home to 697,468 households (over 1.75 million people). The primary purpose of this study was to provide OKI with a new database of travel patterns and behavior to assist in updating the region's transportation models. Respondents were asked to report their activities for a 24-hour period from 3:00 a.m. to 3:00 a.m. on an assigned activity day. The survey included weekday assignments only from October 4, 1995, to November 30, 1995.

1Hz data↗

2006 Greater Triangle Household Travel Survey

The Greater Triangle Household Travel Survey was a comprehensive study of travel behavior throughout the 12-county Research Triangle Region, including all portions of Chatham, Durham, Franklin, Granville, Johnston, Lee, Orange, Person, Wake, and Vance counties, the eastern portion of Harnett County, and the southern portion of Nash County. The primary objective of this survey effort was to document demographic and travel behavior characteristics of regional travelers in order to update the current regional model and to develop a new, more robust travel demand model for the 12-county region. The 2006 survey was conducted in association with NuStats' DataSource and Louis Berger Group and was sponsored by the Capital Area Metropolitan Planning Organization, the Durham-Chapel Hill-Carrboro Metropolitan Planning Organization, the Triangle Transit Authority, and the North Carolina Department of Transportation. The project was conducted over an eleven-month period from August 2005 through June 2006. The survey utilized standard household travel survey methods, in which all household members from 5,107 households were asked to record all trips for a specified 24-hour period using a specially designed travel log on a non-holiday weekday.

1Hz data↗

A Mid-Century Net-Zero Scenario for the State of Wyoming and its Economic Impacts

Clean hydrogen has the potential to help achieve 10% economy-wide emissions reductions by 2050 relative to 2005, promote energy security and resilience, and develop a new economy in the United States. In 2030, the hydrogen economy could create about 100,000 new jobs to build new capital projects and clean hydrogen infrastructure. The Wyoming Energy Authority recently announced the state’s energy strategy, which establishes a goal of net-zero emissions by 2050. Under all likely scenarios, achieving a mid-century net-zero target will pose challenges and create opportunities for Wyoming’s energy sector. If executed properly, the transition could favorably affect the state’s economy overall in the long term. This research program examines the economic impact of fossil energy production in Wyoming and provides various predictions for future energy mixes to achieve net-zero emissions. Preliminary work suggests that Wyoming-based hydrogen production could have significant economic benefits and job creation implications for Wyoming. This study further assesses Wyoming’s opportunities to create hydrogen-based industries, assess economic impacts, identify knowledge gaps and research needs, and create a Hydrogen Center of Excellence to accelerate commercialization and deployment. This project helped to understand Wyoming's areas of focus for research and development and identified its areas of strength and potential challenges in creating a hydrogen ecosystem. As a result of this study, we estimate that for blue hydrogen produced from coal and gas resources, the overall cost reduction will be driven mainly by the carbon-sequestration tax credit and the improvement in carbon capture. Mature technologies, like SMR and PSA, will make limited contributions. They have no or limited reductions from an additional capacity deployment in future costs. We also understand the importance of continued support from public and private sectors for Carbon Capture and Storage (CCS)-related research, development, and demonstration programs at federal and state levels. The successful and efficient production of blue hydrogen requires a unique blend of energy resources, geology, regulation, law, and infrastructure. Wyoming has the distinction of meeting all these demands. The team also estimates that the availability and command of water resources accessible for hydrogen production are crucial for developing new projects. Water treatment, use, and disposal after treatment will also make projects possible. Primarily, this is relevant for hydrogen made using renewable energy. Wyoming has one of the best wind resource capacity in the nation. Harnessing this resource is challenging due to limited transmission line availability. Hydrogen could become one of the solutions to the stranded resource problem, primarily if the water availability challenge is addressed. Using produced oil & gas water could help to solve the problem. A commonly cited barrier to the expansion of hydrogen markets is the cost associated with constructing new pipelines, which typically require large amounts of capital to develop. Wyoming already possesses much of the export infrastructure needed to connect Wyoming’s hydrogen production with major markets across the West Coast, Pacific Northwest, Midwest, and Front Range regions of the United States, where a large portion of Wyoming’s natural gas is already transported. In addition to transportation by pipeline, rail transportation of hydrogen has also proven feasible. Wyoming uses its extensive railway system to transport large amounts of coal to its export partners across the United States. By using cryogenic or compressed-gas cars, Wyoming has the potential to add hydrogen to its existing network of railroad energy exports. The same technology may also be applied to hydrogen transport via trucks traveling interstate highways. Wyoming’s workforce is ready to meet the demands of clean hydrogen development. Many of the skills and training needed for hydrogen production are the same skills already possessed by Wyoming’s oil & gas and coal workforce. Many government and industry leaders expect clean hydrogen and other low-carbon energy projects to generate significant job growth and to recruit many already-trained oil & gas and coal workers whose jobs may be displaced. As energy companies seek to penetrate the markets for Wyoming hydrogen production, there is a natural mutual benefit to Wyoming’s workers and companies seeking to launch projects with the assistance of a trained workforce. Wyoming’s university and community college system have adopted several programs to ensure that highly qualified engineers and other technically skilled employees continue to graduate with skills to support the development of hydrogen and other innovative energy projects moving forward. Throughout the project, stakeholder outreach and education took many forms, including meetings with several major companies in the industry, collaborating with local government organizations, educational organizations, and national laboratories, tribal outreach and engagement, the sponsoring of several hydrogen-focused projects in many departments throughout the University of Wyoming, and developing a collaboration with international universities. The products of these collaborations consist of working relationships with several companies in the industry, educational institutions, national labs, and local government, as well as strong connections with individuals who will play an essential role in the success of the Hydrogen Energy Research Center.

08 HYDROGEN↗

Progress in the development of the community Particle Accelerator Lattice Standard (PALS)

The Particle Accelerator Lattice Standard (PALS) is a community effort to create an open standard to promote lattice information exchange for particle accelerators. PALS development is a community-wide international effort involving accelerator physicists from multiple institutions. While it started as a lattice standard for beam dynamics simulations, it is now being extended to support other particle accelerator activities, in particular accelerator operation. With new accelerators that are becoming more complex, larger collaborations and the increasing imprint of artificial intelligence in all accelerator activities (from design to operation to workforce development), the imperative for a common, standardized accelerator ontology has been transitioning from “nice-to-have” to “must-have”. We will present the status of the project, its relations to other projects, including to two of the particle accelerator projects of the newly announced US DOE Genesis Mission: the Multi-Office Accelerator Team (MOAT) project and the Nuclear physics AI-Ready Accelerator Data (NARAD) project.

Brynes, A. [Science and Technology Facilities Coun↗

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗