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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 523 records · Page 29

Small Signal Point-to-Point Tracking of a Propellant Mixer

This paper addresses some theoretical modelling and control issues for a mixing chamber used in rocket engine testing at NASA Stennis Space Center. The mixer is responsible for combining high pressure LH2 and GH2 to produce a hydrogen flow that meets certain thermodynamic properties before it is fed into a test article. The desired properties are maintained by precise control of the LH2 and GH2 flows. The mixer is modelled as a general multi-flow lumped volume for single constituent fluids using density and internal energy as states. The set of nonlinear differential equations is modelled in the SIMULINK environment including a table look-up feature of the fluid thermodynamic properties. a small-signal (linear) model is developed based on the nonlinear model and simulated as well. Pulse disturbances are introduced to the valve positions and the quality of the linear model is ascertained by comparing its behavior against the nonlinear model simulations. Valve control strategies that simulate an operator-in-the-loop scenario are then explored demonstrating the need for automatic feedback control. Finally, classical optimal single-output and multi-output Proportional/Integral controllers are designed based on the linear model and applied to the nonlinear model with excellent results to track simultaneous, constant setpoint changes in desired exit flow, exit temperature, and mixer pressure, as well as to reject unmeasurable but bounded additive step perturbations in the valve positions.

Barbieri, Enrique↗

Computational Support for Technology- Investment Decisions

Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

Adumitroaie, Virgil↗

Initial Characterization of Optical Communications with Disruption-Tolerant Network Protocols

Disruption-tolerant networks (DTNs) are groups of network assets connected with a suite of communication protocol technologies designed to mitigate the effects of link delay and disruption. Application of DTN protocols to diverse groups of network resources in multiple sub-networks results in an overlay network-of-networks with autonomous data routing capability. In space environments where delay or disruption is expected, performance of this type of architecture (such as an interplanetary internet) can increase with the inclusion of new communications mediums and techniques. Space-based optical communication links are therefore an excellent building block of space DTN architectures. When compared to traditional radio frequency (RF) communications, optical systems can provide extremely power-efficient and high bandwidth links bridging sub-networks. Because optical links are more susceptible to link disruption and experience the same light-speed delays as RF, optical-enabled DTN architectures can lessen potential drawbacks and maintain the benefits of autonomous optical communications over deep space distances. These environment-driven expectations - link delay and interruption, along with asymmetric data rates - are the purpose of the proof-of-concept experiment outlined herein. In recognizing the potential of these two technologies, we report an initial experiment and characterization of the performance of a DTN-enabled space optical link. The experiment design employs a point-to-point free-space optical link configured to have asymmetric bandwidth. This link connects two networked systems running a DTN protocol implementation designed and written at JPL for use on spacecraft, and further configured for higher bandwidth performance. Comparing baseline data transmission metrics with and without periodic optical link interruptions, the experiment confirmed the DTN protocols' ability to handle real-world unexpected link outages while maintaining capability of reliably delivering data at relatively high rates. Finally, performance characterizations from this data suggest performance optimizations to configuration and protocols for future optical-specific DTN space link scenarios.

Space networking↗

Status of the Correlation Process of the V-HAB Simulation with Ground Tests and ISS Telemetry Data

The Virtual Habitat (V-HAB) is a dynamic Life Support System (LSS) simulation, created to investigate future human spaceflight missions. V-HAB provides the capability to optimize LSS during early design phases. Furthermore, it allows simulation of worst case scenarios which cannot be tested in reality. In a nutshell, the tool allows the testing of LSS robustness by means of computer simulations. V-HAB is a modular simulation consisting of a: 1. Closed Environment Module 2. Crew Module 3. Biological Module 4. Physio-Chemical Module The focus of the paper will be the correlation and validation of V-HAB against ground test and flight data. The ECLSS technologies (CDRA, CCAA, OGA, etc.) are correlated one by one against available ground test data, which is briefly described in this paper. The technology models in V-HAB are merged to simulate the ISS ECLSS. This simulation is correlated against telemetry data from the ISS, including the water recovery system and the air revitalization system. Finally, an analysis of the results is included in this paper.

Ploetner, Peter↗

Extending XBAER Algorithm to Aerosol and Cloud Condition

The retrieval of cloud optical properties for aerosol contaminated water cloud is challenging because of the complexity of physical processes in such situations. Conventionally, cloud optical data products are typically derived, ignoring the aerosol impacts on radiative transfer in the retrieval process. This is potentially a significant source of error. In this paper, the eXtensible Bremen Aerosol Retrieval (XBAER) algorithm has been optimized for the retrieval of aerosol/cloud properties for the aerosol contaminated cloud (ACC) scenarios. This version of XBAER delivers cloud optical thickness (COT) and cloud effective radius (CER) for ACCs and simultaneously retrieves aerosol optical thickness (AOT). The surface parameterization and aerosol types used in the standard XBAER algorithm have been adapted in this retrieval to account for the ACC conditions. Aerosol types in XBAER for the retrieval of ACC scenarios have been parameterized to comprise weak and strong absorptions. The comparisons of COT, CER, and AOT retrieved using this adapted XBAER algorithm and two new NASA algorithms show good agreements, especially for biomass burning aerosol. The correlation coefficients are >0.9 for AOT, ~0.8 for CER, and ~0.7 for COT. There is also a good agreement for dust plume contaminated cloud scene. The XBAER derived AOT values for dust aerosols are systematically smaller than the NASA retrieval, but both products have the same spatial distribution patterns. The comparison of COT retrieved using the adapted XBAER algorithm and that retrieved from ground-based microwave radiometer (MWR) measurements shows much better agreement for ACC conditions with high AOT.

satellite↗

Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities.

space traffic management↗

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth-Moon system. Using Multi-Reward Proximal Policy Optimization, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Christopher J Sullivan↗

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

Performance Evaluation of an Advanced Distributed Energy Resource Management Algorithm

This paper presents performance evaluation of a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of sub-transmission and distribution networks, the DERMS software controller, and 84 power hardware solar photovoltaic (PV) inverters, standard communication protocols, and a capacitor bank controller. The DERMS algorithm is also called, Grid-Optimization of Solar (GO-Solar) platform which includes predictive state estimation (PSE) and online multiple objective optimization (OMOO) to dispatch the legacy devices and distributed energy resources (e.g., PV). The voltage regulation performance is evaluated under three scenarios, volt-var smart inverter (baseline), and DERMS control for 100% and 30% of PV. The results show that controlling 30% of PV systems with the GO-Solar platform may provide the best balance of control performance and implementation cost.

distributed energy resource management system (DER↗

Evaluating Nationwide Supply Chain for Circularity of PET and Olefin Plastics

PET (Polyethylene Terephthalate, #1) and olefin plastics including HDPE (High Density Polyethylene, #2), LDPE/LLDPE (Low Density/Linear Low-Density Polyethylene, #4) and PP (Polypropylene, #5) together comprise nearly 80% of the U.S. plastic market. Due to their high market share and extensive application in packaging these polymers have better potential for circularity than other polymer types. To understand the potential of future scenarios with higher recycling rates, supply chain scenarios for PET and olefin plastic packaging need to be analyzed with increased availability and collection of plastics. Currently there exists a knowledge gap to understand the circular supply chain on a national level. Performing a nationwide analysis introduces certain challenges such as variability in the plastic mix of the recycling stream in different municipalities, lack of collection of some types of plastics, regional differences in cost and estimating a national supply curve based on state level access rate and participation rate. Currently, a limited number of Plastic Reclaimers recycle the nation’s collected plastic involving transportation over long distances surpassing state boundaries. Modeling a nationwide scenario instead of regional/state based scenario will facilitate transportation beyond state boundaries for the development of a circular economy. A Mixed-integer Linear Programming model was developed, to identify the optimal location and capacity of the Material Recovery Facilities (MRFs) nationwide subject to maximizing the profit margin of the industrial entities within the model. We considered three different scenarios including the base case scenario (S1) collecting 2.27 million metric tons/year as well as two additional scenarios with available plastic supply of 1.8 times (S2) and 2.2 times (S3) of the base case scenario. The model identified 166, 275 and 319 counties as potential MRF locations for scenarios S1, S2 and S3 respectively. Compared to the existing number of counties having MRFs in the US, the model results indicated a reduction of 38% of MRFs for S1. For S2 and S3, the number of counties with MRFs increased 3% and 20% respectively compared to counties currently with MRFs. The average profit remains constant between $180-$181/ton regardless of the increased plastic collection.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗

Wellbore Stability and Mud Loss Management in Geothermal Drilling: Optimizing Mud Weight to Mitigate Tensile Wellbore Fracturing at The Geysers, California

As part of a U.S. Department of Energy (DOE) Geothermal Technologies Office-funded initiative, Geysers Power Company, LLC, a subsidiary of Calpine Corporation, has been working to enhance drilling performance at the world’s largest geothermal field, The Geysers, in northern California. In a recent drilling operation of the GDC-36 well, excessive mud losses were encountered, initially addressed through repeated but largely ineffective cement plugging. Ultimately, the most effective strategy was to drill blind through the loss zones, made feasible by the high rate of penetration (ROP) achieved with PDC bits, allowing significant progress before the mud tanks were depleted and water-sensitive argillic formation layers could collapse. In response to these challenges, the project team explored alternative methods to minimize downtime and risks associated with cement plugging and continuous mud loss and to contemplate the driving mechanisms for the losses. Wellbore imaging using Formation MicroImager (FMI) and Ultrasonic Borehole Imager (UBI) tools revealed longitudinal tensile fractures, which were attributed to mud weights exceeding the minimum circumferential stress resulting from the native stress field and formation pressure. This study examines the mud losses encountered and leverages wellbore imaging data to understand the mechanisms behind mud induced tensile fracturing in specific rock facies. Understanding fracture behavior across different lithologies is crucial, as fractures within the reservoir can enhance steam migration throughout the system. The reservoir at The Geysers lies within the Mesozoic Franciscan Assemblage, a tectonic mélange formed by subduction. It consists of metamorphosed turbidite sandstone (greywacke) and mudstone (argillite), oceanic upper crust (including greenstone and chert), and serpentinized ultramafic rocks - each exhibiting distinct geomechanical fracturing properties. The structural fabric of the Franciscan Assemblage was shaped by low-angle Mesozoic thrust faulting and later overprinted by sub-vertical strike-slip structures related to the Pacific-North American plate boundary. A wellbore stability model was developed using core measurements and logs to simulate fracturing scenarios during drilling under varying stress conditions. These simulations guided the development of an optimized mud weight management strategy that should enable adaptive adjustments during drilling, reducing the likelihood of tensile fracturing and mud losses, ultimately improving operational efficiency.

15 GEOTHERMAL ENERGY↗

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗

Development of a Distribution Optimal Power Flow Federate for Open-Source OEDI-SI Platform

Increasing numbers of distributed generators in the electric power distribution networks require developing a control strategy to optimize solutions in real time. Linearized optimal distribution flow development has seen growth and acceptance in the distribution systems literature for efficiently modeling the \glspl{opf} for distribution systems. This paper examines the implementation and integration procedure for linearized optimal distribution flow federate to \gls{oedisi} platform. Specifically, we discuss i) the usage of the \gls{oedisi} platform, ii) obtaining a tractable solution using developed \gls{opf} federate, and iii) validation of solutions and bench-marking the \gls{oedisi} platform with developed \gls{opf} federate using OpenDSS. In brief, we demonstrate how a general linearized optimal distribution flow federate can be developed and integrated with a co-simulation environment to mimic real-world examples. The efficacy of the proposed method is demonstrated using the IEEE 123-bus test system under different scenarios to obtain a tractable solution and compare its results.

Sadnan, Rabayet↗

Optimization of the Post-Operational Phase on Two Belgian Multi-Unit Nuclear Power Plants: the Case of the Non-Fissile Irradiated Core Items - 20156

The current legal framework in Belgium foresees the progressive phase out of nuclear power between October 2022 (Doel 3) and December 2025 (Doel 2). Upon its definitive shutdown, each unit of the Tihange and Doel sites will enter a Post-Operational Phase (POP) and be prepared for its Decontamination and Decommissioning (D and D). Prior to obtaining the D and D license, the Operator Electrabel is legally required to remove any non-fissile irradiated core items stored in the deactivation pools. The non-fissile irradiated core items consist essentially of control rods, poison rods and source thimbles as well as thimble plugs and foreign materials irradiated during operation: - Their significant content in highly radiant radionuclides (up to 6 TBq of Co-60 per kg of irradiated material) renders all existing operational waste management processes inadequate due to insufficient biological shielding; - Their high concentrations in long-lived radionuclides call for their disposal in a geological repository for which no final design nor waste acceptance criteria are expected prior to 2050. Uncertainties in the Belgian energy supply and security, however, require the Operator to be prepared for a partial nuclear phase out, where one or more units would benefit from lifetime extension while the remaining units would undergo decommissioning. The present paper aims at presenting how Electrabel, in partnership with Tractebel, addressed this challenge by maximizing the use of synergies within the respective sites as well as between both sites themselves, all the while accounting for site specificities. The most recent results and state of progress of the project will be detailed and the first lessons learned will be shared. The project has been split in multiple tasks and phased as follows: - An inventory phase aimed at mapping the contents, origin, composition and history of the non-fissile irradiated core items; - A pre-characterization phase based on neutron activation models; - A waste sorting phase aimed at separating waste forms for which an evacuation route exists from those for which such route does not exist; - A feasibility phase aimed at exploring all possible scenarios for the management of non-fissile irradiated core items and identifying the optimal feasible solution for each site; - A preparation phase (currently ongoing), developing further the optimal solution and ensuring that back-up solutions are available for any foreseeable change of context (licensing issue, modification in the nuclear phase-out program, etc.) and initiating early contacts with potential subcontractors for segmentation works and cask manufacturers, as well as the Belgian regulatory body and waste management agency. This phase also foresees the investigation of destructive and non-destructive radiological measurements to support the detailed characterization of the waste forms; - A realization phase (future work). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Helicon Plasma Source Optimization Studies for VASIMR

A helicon plasma source at Oak Ridge National Laboratory is being used to investigate operating scenarios relevant to the VASIMR (VAriable Specific Impulse Magnetoplasma Rocket). These include operation at high magnetic field (> = 0.4 T), high frequency (<= 30 MHz), high power (< = 3 kW), and with light ions (He+, H+). To date, He plasmas have been produced with n(sub e0) = 1.7 x 10(exp 19)/cu m (measured with an axially movable 4mm microwave interferometer), with Pin = I kW at f = 13.56 MHz and absolute value of B(sub 0) = 0.16 T. In the near future, diagnostics including a mass flow meter and a gridded energy analyzer array will be added to investigate fueling efficiency and the source power balance. The latest results, together with modeling results using the EMIR rf code, will be presented.

Goulding, R. H.↗

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗

Optimal Sizing of Resilience Solutions for the U.S. Army Reserve

Power or water outages in buildings threaten the ability of the military to support surrounding communities during natural disasters. Outages can last for days, weeks or months. Typical solutions include very expensive batteries and onsite generation that are sized based on historical power needs. The U.S. Army Reserve (USAR) has teamed up with the Pacific Northwest National Laboratory (PNNL) to develop a simulation framework that optimizes future power needs to reduce the cost of resilience solutions. The approach starts with the building. Power needs during an emergency event are simulated at the building end-use level, then loads are reduced through the selection of life cycle cost-effective building-level technology improvements. These new optimized loads are then fed into a microgrid sizing tool that dynamically constructs many different combinations of solar photovoltaic, battery storage, and generator resources to meet the load for hundreds of statistically generated outage scenarios. Six site assessments completed by USAR and PNNL in 2019 have resulted in a 1-14% reduction in overall investment when optimizing the buildings first before determining the generation requirements. This approach helps the Army secure critical missions and provide a 14 day-minimum supply of necessary energy and water in the most efficient manner.

buidlings, efficiency, resilience, FEDS, MCOR↗