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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Qualitative Description of Electric Power System Future States

This work proposes a common basis for the simulation and evaluation of transactive systems. Using existing literature, a qualitative survey of the future states of the electric power system was conducted. Forces exerting influence on the state of the power system, called “drivers,” were identified. Specific future states in the literature were identified and classified into five general groups, and the effects of twelve previously identified drivers were assessed for each individual future state in the literature. Relationships between the five general future states were defined through a Venn diagram and system evolutions were demonstrated through notional narratives and corresponding paths through the diagram. A relational measure of the complexity and extent of the change implied by each future state was also created.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Current and Future United States Light-Duty Vehicle Pathways: Cradle-to-Grave Lifecycle Greenhouse Gas Emissions and Economic Assessment

This article presents a cradle-to-grave (C2G) assessment of greenhouse gas (GHG) emissions and costs for current (2015) and future (2025–2030) light-duty vehicles. The analysis addressed both fuel cycle and vehicle manufacturing cycle for the following vehicle types: gasoline and diesel internal combustion engine vehicles (ICEVs), flex fuel vehicles, compressed natural gas (CNG) vehicles, hybrid electric vehicles (HEVs), hydrogen fuel cell electric vehicles (FCEVs), battery electric vehicles (BEVs), and plug-in hybrid electric vehicles (PHEVs). Gasoline ICEVs using current technology have C2G emissions of ~450 gCO2e/mi (grams of carbon dioxide equivalents per mile), while C2G emissions from HEVs, PHEVs, H2 FCEVs, and BEVs range from 300–350 gCO2e/mi. Future vehicle efficiency gains are expected to reduce emissions to ~350 gCO2/mi for ICEVs and ~250 gCO2e/mi for HEVs, PHEVs, FCEVs and BEVs. Utilizing low-carbon fuel pathways yields GHG reductions more than double those achieved by vehicle efficiency gains alone. Levelized costs of driving (LCDs) are in the range $0.25–$1.00/mi depending on timeframe and vehicle-fuel technology. In all cases, vehicle cost represents the major (60–90%) contribution to LCDs. Currently, HEV and PHEV petroleum-fueled vehicles provide the most attractive cost in terms of avoided carbon emissions, although they offer lower potential GHG reductions The ranges of LCD and cost of avoided carbon are narrower for the future technology pathways, reflecting the expected economic competitiveness of these alternative vehicles and fuels.

Cradle-to-grave↗

Future Grid State Modeling for Transactive Systems

The simulation design and evaluation of a transactive energy system is contingent on the setting in which it would exist, which could vary significantly with the many drivers that impact the potential future states of the power system. This report summarizes the development of the Transactive Future Grid State (TFGS) model, which is a lightweight capacity expansion model that will support transactive energy research by allowing users to explore alternative future states. The TFGS model determines the long-term generation capacity needs of a given power system that satisfy specified constraints and support a least cost hourly dispatch. This is accomplished by solving a single optimization problem that simultaneously finds the generation fleet with capacity sufficient to meet peak load and the flexibility to meet hourly operational dispatch, all at lowest cost. The TFGS model was applied to a larger ongoing study taking place that will be simulating how distribution system operators (DSOs) could use a transactive energy system to manage distributed energy resources. The larger study, commonly referred to as the DSO+T study, involves two parallel analyses; one that represents the system today and one that represents a future system with a high degree of renewable energy penetration. The TFGS model provided the generation mix of the high renewable base case. As the TFGS model was being used to provide inputs to the DSO+T study, two issues became apparent. First, additional functionality would have been useful, and second, a larger-than-anticipated amount of user inputs and data were required to successfully use the TFGS model. These discoveries have lead to the recommendation of specific functionality that can be added in future development of the tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The future of natural gas infrastructure development in the United states

Changes in the natural gas market have spawned the need for pipeline infrastructure planning. Previous studies have analyzed natural gas infrastructure development largely independent of the interactions of the natural gas sector with the broader economy. However, natural gas infrastructure development is strongly influenced by broader domestic and international socioeconomic conditions. We couple a global Human-Earth system model with state-level detail in the United States (GCAM-USA) that provides the broader socioeconomic context for natural gas supply and demand with a natural gas infrastructure investment model (NANGAM) to examine interstate natural gas pipeline infrastructure development in the U.S. under a range of socioeconomic scenarios. Here we show that existing pipeline infrastructure in the U.S. is insufficient to satisfy the increasing demand for natural gas and investments in pipeline capacity will be required. However, the geographic distribution of investments within the U.S. is heterogeneous and depends on the capacity of existing infrastructure as well as the magnitude of increase in demand. Our results also illustrate the risks of under-utilization of pipeline capacity, in particular, under a scenario characterized by long-term systemic transitions toward a low-carbon economy. More broadly, our study highlights the value of integrated approaches to facilitate informed decision-making.

Feijoo, Felipe↗

Bayesian inference of fine features of the nuclear equation of state from future neutron star radius measurements to 0.1 km accuracy

To more precisely constrain the equation of state (EOS) of supradense neutron-rich nuclear matter, future high-precision x-ray and gravitational wave observatories are proposed to measure the radii of neutron stars (NSs) with an accuracy better than about 0.1 km. However, it remains unclear what particular aspects (other than the stiffness generally spoken of in the literature) of the EOS and to what precision they will be better constrained. In this work, within a Bayesian framework using a metamodel EOS for NSs, we infer the posterior probability distribution functions (PDFs) of incompressibility K 0 and skewness J 0 of symmetric nuclear matter (SNM) as well as the slope L, curvature K sym , and skewness J sym characterizing the density dependence of nuclear symmetry energy E sym ⁡(ρ), respectively, from mean values of NS radii consistent with existing observations and an expected accuracy Δ⁢R ranging from about 1.0 to 0.1 km. Here, we found that (1) the Δ⁢R has little effect on inferring the stiffness of SNM at suprasaturation densities, (2) smaller Δ⁢R reveals more accurately not only the PDFs but also pairwise correlations among parameters characterizing high-density E sym ⁡(ρ), (3) a double-peak feature of the PDF(K sym ) corresponding to the strong K sym – J sym and K sym – L anticorrelations is revealed when Δ⁢R is less than about 0.2 km, and the locations of the two peaks are sensitive to the maximum value of J sym reflecting the stiffness of E sym ⁡(ρ) above about 3 times the saturation density ρ 0 of SNM, and (4) the high-precision radius measurement for canonical NSs is more useful than that for massive ones for constraining the EOS of nucleonic matter around (2–3)⁢ρ 0 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ventenata dubia projected to expand in the western United States despite future novel conditions

Abstract Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata ( Ventenata dubia ) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas. Climate novelty did not appear to undermine the prediction reliability in many cases where the climate–species relationship was fully represented by the occurrence data. GCM‐derived variability resulting from variation in future cool season precipitation and temperature seasonality was greatest in the Rocky Mountains. SDM‐derived variability was higher in currently suitable habitat, and few GCMs projections agreed that these areas would contain future suitable habitat. However, while prediction variability was high, many GCM projections agreed that parts of the Rocky, Wasatch, and Uinta Mountains would contain highly suitable habitat in the future. As disturbances in the interior mountains occur in coming decades, reducing some natural barriers to invasion, land managers, and conservationists will need to monitor for ventenata in post‐disturbance environments. Changes to invasion potential may not play out for several decades, but results related to current potential may have applications for early detection and rapid response planning.

Environmental Sciences & Ecology↗

Estimating and Forecasting Time-Varying Groundwater Recharge in Fractured Rock: A State-Space Formulation with Preferential and Diffuse Flow to the Water Table

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

groundwater, Recharge, infiltration, recursive est↗

Advanced Controls for the Multi-pod Centipod WEC device

Dehlsen Associates, LLC (DA) has developed a Wave Energy Converter (WEC), Centipod, which is a multiple point absorber, extracting wave energy primarily in the heave direction through a plurality of point absorber floats sharing a common stable reference structure. The objective of this project was to develop advanced control algorithms that will be used to reduce Levelized Cost of Energy (LCOE). This project investigated the use of Model Predictive Control (MPC) to improve the power capture of the WEC. The MPC controller developed in this work is a state-space, “look ahead” controller approach using knowledge of past and current states to predict future states to take action with the PTO to maximize power capture while still respecting system constraints. In order to maximize power, which is the product of force and velocity, the controller must aim to create phase alignment between excitation force and velocity. This project showed a 161% improvement in the Annual Energy Production (AEP) for the Centipod WEC when utilizing MPC, compared to a baseline, fixed passive damping control strategy. This improvement in AEP was shown to provide a substantial benefit to the WEC’s overall Cost of Energy, reducing LCOE by 50% from baseline. The results of this work proved great potential for the adoption of Model Predictive Controls in Wave Energy Converters.

16 TIDAL AND WAVE POWER↗

Future Electric Power Industry and Grids—Now What Again is Our Destination?

Having a vision that others agree to support and work toward is highly desirable but hard to achieve. We seem to lack a common and shared understanding of the vision—or worse, multiple visions (vivid mental images or documented statements) with varying areas of focus and details: • some appear to be similar but have differing underlying goals and characteristics, or • some reflect differing viewpoints as to effects on various stakeholders. These desirable and undesirable situations apply to realizing visions for enterprise and industry, including the electricity sector. Multiple industry stakeholder groups have developed goals, industry vision statements, and characterizations of the future. The viewpoints are promoted, discussed, refined by their stakeholder group, and often published to promote broad understanding and to inform or influence others. The GridWise Architecture Council asked itself how well-aligned these characterizations of the future are. If these publications collectively set the overall direction for the industry, it is useful to identify their answers to questions such as, where is the electric industry headed, guided by what objectives, and with what role(s) for the customers, electric utilities, and other stakeholders? Are these goals, visions, and future states moving toward a common vision, do they provide value for the stakeholders, and are they likely to meet the objective stated? This paper addresses these questions via an assessment and characterization of a sampling of stakeholder groups’ publicly available vision and future state reports for the electricity industry. Identified electric power grid architectural topic areas needing further work are described, along with GridWise Architecture Council analysis and observation, potential collaborative work efforts, and suggested next steps.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Current state and future projections of drying processes in the US food and pulp and paper sectors: Energy, economic, and environmental assessment

The pulp and paper (P/P) and food sectors are the third- and fifth-largest industrial energy consumers in the United States, with total on-site energy consumption of 2,039 TBtu and 1,144 TBtu, respectively. Thermal drying processes for moisture removal, which are energy-intensive, play a critical role in both industries. This study is the first to evaluate state- and national-level US drying energy demand for these sectors from 2020 to 2050. To complete this evaluation, we developed a thermodynamic modeling framework integrated with economic and environmental models to compute product-specific drying energy intensity and estimate the sector-specific costs and emissions profiles associated with drying operations. The model-predicted energy intensity was validated against the literature. Using current and projected annual production volumes in these sectors, we estimated total drying energy use. Results indicate that drying accounts for 22 % of total energy consumption in the P/P sector and 10 % in the food sector. The estimated annual energy cost (2020) to operate thermal dryers is $\$$919 M in the P/P sector and $\$$417 M in the food sector. Additionally, drying contributes to 25 % of total CO 2 e emissions in the P/P sector (including biogenic) and 15 % of emissions in the food sector. Regional performance shows that the Southern US is the leading energy consumer for P/P drying, whereas the Midwest leads in food drying. This study presents both potential solutions to enhance drying efficiency and barriers to implementation. Energy efficiency improvements, low-carbon fuels, and electrification are discussed as key pathways for reducing costs and optimizing industrial drying processes.

3E analysis↗

Review of the Third Conference of the Imaging Mass Spectrometry Society (IMSS 3): Accounts of a Hybrid Virtual and In-Person Meeting and the State and Future of the Field

The third annual conference of the Imaging Mass Spectrometry Society (IMSS3) was held October 3–6, 2021 in a hybrid format that included virtual and in-person attendance (Colorado Springs, CO). In this work, we highlight many of the methods and applications presented, the state of the field, and some insights into the emerging areas in the field of imaging mass spectrometry. We also reflect upon the processes behind planning a hybrid conference and discuss the successes and challenges of the event in retrospect.

47 OTHER INSTRUMENTATION↗

Nanocellulose Dewatering and Drying: Current State and Future Perspectives

The knowledge base for nanocellulose (NC) has grown exponentially over the past two decades and continues to expand with the increasing number of potential applications demonstrated in the literature and the patent space. NC has multiple forms depending on the starting cellulose source and the specific process used to produce it. Its high degree of surface reactivity makes it an ideal support structure for a wide variety of functional groups, leading to the ability to engineer materials for very specific applications. However, removing water from an NC suspension, e.g., dewatering and drying, while retaining the nanoscale properties of the NC remains a significant challenge to successful commercialization of NC materials. Processes for dewatering and drying of NC are desirable because of the high transport costs of shipping dilute aqueous suspensions, as well as end-use application requirements. Therefore, the development of nondestructive, cost-effective, scalable, and environmentally friendly dewatering and drying processes is important for commercial deployment of NC applications. This review addresses the current state of published knowledge on NC dewatering and drying and identifies research gaps that could be further explored in a precompetitive context to accelerate commercialization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Acidification in the Southern Ocean – current state and future challenges

The Southern Ocean is especially sensitive to ocean acidification, a process where carbon dioxide in the atmosphere is absorbed by the ocean, thereby changing its acidity levels. Observations show that open ocean waters across the Southern Ocean experienced faster rates of acidification over the past four decades than non-polar waters. Model simulations project more severe ocean acidification in Antarctic coastal waters than in the open ocean. Ocean acidification negatively impacts many Southern Ocean species, but our understanding of whole-ecosystem impacts is incomplete. Furthermore, it is important that we both maintain and expand observational capabilities and mechanistic experiments in this rapidly changing and vulnerable region of the ocean to understand the impacts of ocean acidification on Southern Ocean ecosystems.

Nissen, Cara [University of Amsterdam (The Netherl↗

Engineering microbial consortia for controllable outputs

Much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into resilient consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here, we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution global measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that when combined with appropriate modeling framework that predictive knowledge generates testable hypotheses and orthogonal synthetic biology tools, such understanding can dramatically improve our ability to control the fate and functioning of consortia. In this article, we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties.

controllable outputs↗

Equation-based and data-driven modeling: Open-source software current state and future directions

Here, a review of current trends in scientific computing reveals a broad shift to open-source and higher-level programming languages such as Python and growing career opportunities over the next decade. Open-source modeling tools accelerate innovation in equation-based and data-driven applications. Significant resources have been deployed to develop data-driven tools (PyTorch, TensorFlow, Scikit-learn) from tech companies that rely on machine learning services to meet business needs while keeping the foundational tools open. Open-source equation-based tools such as Pyomo, CasADi, Gekko, and JuMP are also gaining momentum according to user community and development pace metrics. Integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to radically accelerate progress. However, long-term support mechanisms are still necessary to sustain the momentum and maintenance of critical foundational packages.

97 MATHEMATICS AND COMPUTING↗