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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

High Performance Computing Facility Operational Assessment 2015: Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security aspects associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2015 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction that ties the highest-ever mark set in CY 2014; the greatest number of core-hours delivered to research projects; the largest percentage of capability usage since the OLCF began tracking the metric in 2009; and success in delivering on the allocation of 60, 30, and 10% of core hours offered for the INCITE (Innovative and Novel Computational Impact on Theory and Experiment), ALCC (Advanced Scientific Computing Research Leadership Computing Challenge), and Director’s Discretionary programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations. The impact of all of these successes and more is reflected in the accomplishments of OLCF users, with publications this year in notable journals Nature, Nature Materials, Nature Chemistry, Nature Physics, Nature Climate Change, ACS Nano, Journal of the American Chemical Society, and Physical Review Letters, as well as many others. The achievements included in the 2015 OLCF Operational Assessment Report reflect first-ever or largest simulations in their communities; for example Titan enabled engineers in Los Angeles and the surrounding region to design and begin building improved critical infrastructure by enabling the highest-resolution Cybershake map for Southern California to date. The Titan system provides the largest extant heterogeneous architecture for computing and computational science. Usage is high, delivering on the promise of a system well-suited for capability simulations for science. This success is due in part to innovations in tracking and reporting the activity on the compute nodes, and using this information to further enable and optimize applications, extending and balancing workload across the entire node. The OLCF continues to invest in innovative processes, tools, and resources necessary to meet continuing user demand. The facility’s leadership in data analysis and workflows was featured at the Department of Energy (DOE) booth at SC15, for the second year in a row, highlighting work with researchers from the National Library of Medicine coupled with unique computational and data resources serving experimental and observational data across facilities. Effective operations of the OLCF play a key role in the scientific missions and accomplishments of its users. Building on the exemplary year of 2014, as shown by the 2014 Operational Assessment Report (OAR) review committee response in Appendix A, this OAR delineates the policies, procedures, and innovations implemented by the OLCF to continue delivering a multi-petaflop resource for cutting-edge research. This report covers CY 2015, which, unless otherwise specified, denotes January 1, 2015, through December 31, 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Implementing the Inflation Reduction Act: What We Expect and How We Might Get There

This presentation summarizes findings from three related studies: Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System; The Roles and Impacts of PV-Battery Hybrids in a Decarbonized U.S. Electricity Supply; and Optimal Design and Deployment of Wind-Solar Hybrids in Low-Carbon U.S. Power System. The compilation of results from these three studies indicate that the Inflation Reduction Act could drive significant deployment of variable renewable energy technologies, but the level of deployment depends on our ability to build new transmission projects (among other factors). Hybrid systems can help, to an extent, to facilitate greater shares of wind/solar with lesser amounts of transmission expansion.

Bipartisan Infrastructure Law↗
DOE OSTI2021

Distributed deep reinforcement learning for simulation control

Abstract Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4 Data and codes available at https://github.com/Romit-Maulik/PAR-RL . .

42 ENGINEERING↗
DOE OSTI2018

Bimetallic synergy in cobalt–palladium nanocatalysts for CO oxidation

Bimetallic and multi-component catalysts often exhibit superior activity and selectivity compared with their single-component counterparts. To investigate the origin of the composition dependence observed in the catalytic activities of CoPd bimetallic catalysts, the compositional and structural evolution of monodisperse CoPd alloy nanoparticles (NPs) were followed under catalytic CO oxidation conditions using ambient pressure X-ray spectroscopy (AP-XPS) and transmission electron microscopy (TEM). It was found that the catalysis process induced a reconstruction of the catalysts, leaving CoOx on the NP surface. The synergy between Pd and CoOx coexisting on the surface promotes the catalytic activity of the bimetallic catalysts. Such synergistic effects can be optimized by tuning the Co/Pd ratios in the NP synthesis and reach a maximum at compositions near Co 0.26 Pd 0.74 , which exhibits the lowest temperature for complete CO conversion. Our combined AP-XPS and TEM studies provide a direct observation of the bimetallic NPs surface evolution under catalytic conditions and its correlation to catalytic properties.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

HPC for the EEC: Industrial Trade Tools for the Aging Energy Infrastructure

The petrochemical and refining sectors are challenged with reliably delivering safer and cleaner energy to US consumers, while meeting an ever-growing global demand. The petrochemical and refining infrastructure in the USA is aging, and corrosion and damage mechanisms are constant threats to mechanical integrity, safety, and profitability. However, governments and industry stakeholders are reluctant to replace or upgrade the existing infrastructure due to the immense cost. To better understand and mitigate the risks of aging energy infrastructure, strong technical analysis capabilities, combined with optimized monitoring and decision making, is critical. Today, this is accomplished via complex simulations and data analysis. To this end, advanced High-Performance-Computing (HPC) software will be leveraged and integrated in easy-to-use industrial trade tools, to lower the barrier for new users, increase the ease of access for experienced users, and allow for smarter decisions to be made in the midstream and downstream energy sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Cost Benefit Analyses through Integrated Online Monitoring and Diagnostics (Final Report)

The objective of this research is to improve the economic competitiveness of advanced reactors through the optimization of cost and plant performance, which can be achieved by coupling intelligent online monitoring with asset management decision-making. As advanced reactors are early in the development life-cycle, online monitoring systems and associated sensor networks can be incorporated directly into the design without constraints related to retrofitting and system upgrades

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Uranus Probe Entry and Descent Mission Concept

Introduction: Uranus was identified as the third highest priority flagship mission in the 2012-2022 Planetary Science Decadal Survey. This latest concept study was requested by the Decadal Survey panel to determine NASA’s planetary science priorities from 2022-2032. This study focused on the probe’s entry and descent aspects and associated trades for viable trajectory options. Uranus Mission and Descent Probe: The proposed Uranus Orbiter and Probe (UOP) Flagship mission will investigate Uranus and its surrounding moons using an orbiting spacecraft with a Uranus descent probe. Unlike previous studies the probe release will occur after orbit insertion allowing sufficient separation of critical events during the orbit insertion burn. The probe will be released at an altitude that allows one hour of in situ atmospheric readings that will be relayed to the orbiter. Afterwards the orbiter will transition to the moon tour phase of the mission. The configuration chosen for the entry aeroshell was a 45° sphere-cone. This shape has been used in the past in the Pioneer Venus Galileo missions. However, the nose radius considered in the present study differed from the values used in either of the previous configurations, primarily to reduce the heat flux at the stagnation point. A two-step approach was used in the development of flight trajectories for the chosen configuration. In the first step, the trajectory code POST2 was used to screen the thousands of entry states provided by interplanetary trajectory simulations, which were terminated at an altitude of 2000 km from the reference surface (1 bar) of Uranus. The screening criteria were: (i) optimization of the communication geometry between the entry probe and orbiter to ensure at least 1 hour of science measurements, (ii) peak stagnation point pressures to be less than six bar, (iii) peak heat fluxes to be less than 5 kW/cm2; the latter two constraints being the limits of ground-test capabilities of the arc jets at NASA Ames Research Center. The entry team investigated two trajectories that met the criteria above, a shallow entry (high heat load ~44 kJ/cm2) and a steeper entry (high heat rate ~1950 W/cm2). In the second step, the two bounding candidate entry states from the POST2 screening process were used in developing flight trajectories using TRAJ coupled with FIAT (a materials thermal response and sizing code) and a margins policy to determine a margined uniform thickness (hence mass) of the forward heatshield material based on the aerothermal environments at the stagnation point. Since the combination of TRAJ and FIAT size the TPS based on stagnation point environments only, flow field computations using DPLR were necessary to determine turbulent aerothermal environments on the conical flank, and the augmentation of these environments due to surface roughness. The environments at select locations on the forward heatshield were then used to size the thermal protection material, with the largest thickness value then used to estimate the mass. The newly developed woven thermal protection material –HEEET (Heatshield for Extreme Entry Environments Technology) –was considered for the forward heatshield and PICA (Phenolic-Impregnated Carbon Ablator) was considered for the backshell. These NASA-developed materials are at TRL 6 and TRL 9, respectively. Furthermore, two options were considered for the HEEET material: (i) a dual-layer option with a denser recession layer on top and an insulative layer underneath it, and (ii) a single layer option consisting of the insulative layer alone. Results: It is clear that probe entry states are feasible and the selected TPS options are able to perform in the predicted aerothermal environments thus enabling the mission to meet of the descent probe portion of this flagship mission

Entry Descent and Landing↗
DOE OSTI2013

R and D Programs and Policy within the CEA-AREVA Joint Vitrification Lab (LCV) - 13592

Waste management is a key issue for the reprocessing industry; furthermore, vitrification is considered as the reference for nuclear waste management. In order to further improve and strengthen their historical cooperation in high temperature waste management, the CEA, R and D organization, and AREVA, Industrial Operator, decided, in September 2010, to create a Joint Vitrification Laboratory within the framework of a strategic partnership. The main objectives of the CEA-AREVA Joint Vitrification Laboratory (LCV) are (i) support AREVA's activities, notably in its La Hague plants and for new projects, (ii) strengthen the CEA's lead as a reference laboratory in the field of waste conditioning. The LCV is mandated to provide strong, innovative solutions through the performance of R and D on processes and materials for vitrification, fusion and incineration, for high, intermediate and low level waste. The activities carried out in the LCV include academic research on containment matrices (formulation, long-term behaviour), and the improvement of current technologies/development of new ones in lab-scale to full-scale pilot facilities, in non-radioactive and radioactive conditions, including modelling and experimental tools. This paper focuses on the programs and policy managed within the LCV, as well as the means employed by the CEA and AREVA to meet common short-,mid- and long-term challenges, from a scientific and industrial point of view. Among other things, we discuss the technical support provided for the La Hague vitrification facilities on hot melter and CCIM technologies, the start-up of new processes (decommissioning effluents, UMo FP) with CCIM, the preparation of future processes by means of an assessment of new technologies and containment matrices (improved glasses, ceramics, etc.), as well as incineration/vitrification for organic and metallic mixed waste or metallic fusion. The close relationship between the R and D teams and industrial operators enables the LCV to propose attractive waste management solutions, with appropriate schedules and optimized development costs, making allowance for R and D constraints, engineering requirements and the industrial environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

The CPAT Domain Model - How CPAT "Thinks" from an Analyst Perspective

To help effectively plan the management and modernization of its large and diverse fleet of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) commissioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This report contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Enhancing Power Resilience for Remote Communities: A Comprehensive Renewable Energy Solution for Itbayat Island

The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.

14 SOLAR ENERGY↗
DOE OSTI2023

Optimizing Performance on Trinity Utilizing Machine Learning, Proxy Applications and Scheduling Priorities

The sheer number of nodes continues to increase in today’s supercomputers, the first half of Trinity alone contains more than 9400 compute nodes. Since the speed of today’s clusters are limited by the slowest nodes, it more important than ever to identify slow nodes, improve their performance if it can be done, and assure minimal usage of slower nodes during performance critical runs. This is an ongoing maintenance task that occurs on a regular basis and, therefore, it is important to minimize the impact upon its users by assessing and addressing slow performing nodes and mitigating their consequences while minimizing down time. These issues can be solved, in large part, through a systematic application of fast running hardware assessment tests, the application of Machine Learning, and making use of performance data to increase efficiency of large clusters. Proxy applications utilizing both MPI and OpenMP were developed to produce data as a substitute for long runtime applications to evaluate node performance. Machine learning is applied to identify underperforming nodes, and policies are being discussed to both minimize the impact of underperforming nodes and increase the efficiency of the system. In this paper, I will describe the process used to produce quickly performing proxy tests, consider various methods to isolate the outliers, and produce ordered lists for use in scheduling to accomplish this task.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Support for Reactor Operators in Case of Cyber-Security Threats (NEUP Final Report)

Increasing use of digital technology in nuclear power plants (NPPs) poses cyber-security as a crucial threat to public safety and to continuous energy production. Cyber-security risks are comprised of complex known and unknown interactions between various entities, system vulnerabilities, network protocols, human users and malicious attacks. There is little understanding or research geared towards plant operators’ response under cyber-security threats and operational procedures to cope with such threats. This is particularly critical when a cyber-security event masquerades as a safety incident or an evolving accident. Instead of leading operators to the remediation of the accident, the masked cyber event may lead them to circumvent the safety mechanisms of the plant. Given these challenges, the objective of this project is to develop a tool to characterize abnormal NPP events as “cyber” or “safety” incidents, and to further develop this tool as a real-time operator aid to assist in response to the incident. This NEUP Final Report summarizes the research efforts towards the above goals and the results in the following three aspects. First, a methodology for classifying abnormal NPP events as cyber-attacks or safety incidents was developed. This provides the basis for responding to potential cyber-attacks. In this methodology, the causal relationships between various variables (i.e., physical variables, network variables, and control variables) for a nuclear system under consideration are modeled using dynamic Bayesian networks. Based on observations of certain variables (i.e., the evidence), inference is performed to identify the state of hidden variables, which helps indicate the occurrence of cyber-attacks or safety incidents. The proposed methodology was applied to the full scope NPP simulator system at The Ohio State University as a case study. The result shows that the proposed methodology is capable of distinguishing between cyber-attacks and safety incidents. Second, a game-theoretic approach for responding to cyber-attacks on nuclear power plants was developed. This is the second major goal of the project, and the method is used to recommend optimal responses to reactor operators in the case of cyber-attacks. We consider two cases in this research. In the first case, the interaction between the defender (i.e., the reactor operator) and the attacker is modeled as a two-player, nonzero-sum, Markov game with an infinite time horizon. In the second case, we consider a semi-Markov game between the defender and the attacker within a finite time horizon. The model in the second case enables us to consider the time sensitive response of the defender. In each case, the method for deriving the Nash equilibrium is developed. The Nash Equilibrium of the game provides the valid prediction of both players’ actions because no single player can benefit from unilaterally deviating from the equilibrium policy if the other player adheres to his/hers, hence it provides the best response of the defender to cyber-attacks. The proposed method in each case is demonstrated through a simplified benchmark digital feedwater control system. Third, a prototype display is developed to integrate the above information. The prototype display depicts the communication information to the operator and incorporates the cyber-security tool developed by the team into the interface. It consists of the regular display in current control rooms, as well as a panel used to indicate the occurrence of cyber-attacks or safety events and a panel used to guide the operator’s response to detected cyber-attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

NASA's Efforts to Commercialize Communications Services for Mission in Near-Earth Space

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation (SCaN)Program enables high speed, robust, secure and cost-effective space communications and navigation services to current and future science and exploration missions. Consistent with National Space Policy, NASA is pursuing the use of demonstrated commercial services for all its future near-Earth requirements through a flexible, multi-provider approach that minimizes risks to the user missions and ensures costs to user missions are reasonable. Progress toward this goal is advancing in multiple key areas including direct to Earth (DTE), space-based relay, technology investments, required spectrum regulatory changes and mission engagement and infusion. The transition to commercial DTE services is already underway, with a target for transition by 2024. The primary functions to execute SCaN’s DTE strategy include increasing commercial service allocations by leveraging current commercial network providers and enabling seamless onboarding of additional providers into the network. Furthermore, moving away from government DTE services will allow operational costs to be optimized. A more gradual approach is planned for the transition to commercial space-based relay services to allow for demonstration and operationalization of commercial services for future users by 2030. In June of 2022, six American SATCOM vendors were awarded a combined $278.5 million through Funded Space Act Agreements (FSAAs) for the first cycle of demonstration and validation activities. The end-to-end service capabilities being targeted are based on existing NASA mission operational needs. Accordingly, each company has proposed a technical approach to lower costs, increase flexibility, and improve performance for a broad range of missions. Successful user mission transition to commercial services, both DTE and space-based relay, are dependent on the technologies and capabilities that address gaps in commercial capability. NASA is investing in technology development and pursuing a new strategic approach to the creation or adoption of space communications standards to move the agency toward a commercial paradigm. Wideband and multi-lingual user terminals are being developed to bridge differences in industry services. Building on ground demonstrations completed in 2021, the Johns Hopkins Applied Physics Lab (APL) will be flight testing a multi-lingual wideband terminal (payload) and demonstrating connectivity to both government and commercial relay services. NASA holds a leadership role in multiple civil space standards bodies and international coordination groups to ensure that standards supporting interoperability are developed with defined functions, interfaces, and performance. However, to successfully meet commercialization objectives, NASA seeks to collaborate with industry, and as applicable adopt or adapt to commercially defined standards. As such, NASA joined the 3rd Generation Partnership Project (3GPP) as an official member in 2021 to advocate for the inclusion of space missions as a unique user segment in future 5G non-terrestrial networks, and to better understand the scope of 3GPP releases and implications for space users. Further, engagement in Spectrum regulatory bodies is being undertaken to augment existing space-Earth and inter-satellite frequency allocations available for both government and commercial space systems. This paper addresses the recent progress toward NASA’s commercial space communications transition objectives and how key challenges are being navigated.

Gregory W Heckler↗
DOE OSTI2016

Systems and methods for energy cost optimization in a building system

Methods and systems to minimize energy cost in response to time-varying energy prices are presented for a variety of different pricing scenarios. A cascaded model predictive control system is disclosed comprising an inner controller and an outer controller. The inner controller controls power use using a derivative of a temperature setpoint and the outer controller controls temperature via a power setpoint or power deferral. An optimization procedure is used to minimize a cost function within a time horizon subject to temperature constraints, equality constraints, and demand charge constraints. Equality constraints are formulated using system model information and system state information whereas demand charge constraints are formulated using system state information and pricing information. A masking procedure is used to invalidate demand charge constraints for inactive pricing periods including peak, partial-peak, off-peak, critical-peak, and real-time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Formal methods approach to the charging facility location problem for battery electric vehicles

Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Improved Advanced Biomass Logistics Utilizing Woody and other Feedstocks in the Northeast and Pacific Northwest (Final Report)

Willow and poplar short rotation woody crops (SRWC) have shown promise with regards to environmental benefits and rural development but wide adoption lags due to underdeveloped markets and supply systems. High costs associated with harvesting, handling and transportation (40-60% of delivered cost) have impeded expansion. A better understanding of these systems will create opportunities to improve efficiency, reduce costs, and realize environmental benefits and impacts. The project’s goal was to lower the delivered cost of hybrid poplar in the Northwest and willow in the Northeast by optimizing harvesting and logistics supply systems while maintaining or improving biomass quality along the supply chain. Over 3,400 Mg of biomass and 300 ha of willow and poplar were monitored over a range of crop and field conditions. Feedstock quality as affected by storage and preprocessing were shown to improve or maintain feedstock quality. Modeled harvesting costs ranged from $38–61 Mg -1 dry; when including delivery and preprocessing feedstock costs ranged between $79-83 Mg -1 dry for willow and $106-116 Mg -1 dry for poplar. Costs for willow minimized when hot water extraction and high-moisture densification preprocessing were used. Models also suggest that social and regional factors could further reduce costs. Results will give guidance to feedstock growers, harvesting and logistic operations, biorefinery project developers, and policy makers developing SRWC to support a growing bioeconomy.

, biomass↗
DOE OSTI2025

Project Planning for Community Resilience: Aquinnah and Chilmark, Massachusetts

This report presents the findings of an energy system planning study for the towns of Aquinnah and Chilmark, MA, on the island of Martha’s Vineyard, conducted under the U.S. Department of Energy ETIPP program. The study used the DER-CAM model to optimize the deployment of PV and battery microgrids to enhance energy resilience against power outages, particularly winter storms. Key findings show that PV is highly cost-effective and delivers net annual savings. However, due to limited rooftop space and low winter solar output, PV and battery storage alone cannot support the full critical load during outages. Solutions incorporating conventional backup generators were found to be more economically viable for achieving 100% critical load support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗