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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗
DOE OSTI2024

Cyber-Physical System: Design for Sustainability and Resilience

When considering the design tools needed in the transition from numeric models to pilot plant, cyber-physical systems (CPS) come to the forefront as a method to model complex integrated energy systems. CPS approach has proven to be valuable to identify opportunities for economically viable early adoption of integrated energy technologies. This tutorial will introduce the concepts and the roles of CPS in co-design to minimize risks for pilot plant and technology deployment. This tutorial will also layout basic requirements for the CPS development, which requires a highly interdisciplinary effort with expertise in sensors, hardware testing, real-time modeling, controls, and system integration.

Harun, Nor Farida↗
DOE OSTI2018

Packed and fluidized bed absorber modeling for carbon capture with micro-encapsulated sodium carbonate solution

Micro-Encapsulated CO 2 Sorbents (MECS) are a promising technology for post-combustion carbon capture because they enable slow-reacting solvents like carbonate solution to compete with traditional amine solvents. Before scaling up MECS for pilot testing, modeling is needed to design a MECS absorber and quantify its size and energy penalty. To that end, a multi-scale model for MECS- that ranges from a single capsule to a 500 MWe power plant absorber- is developed and presented here in this paper. First, the individual capsule model is developed and fitted to experimental CO 2 absorption data collected on a 0.1 g sample of capsules filled with sodium carbonate solution. This capsule model is then validated against data collected on a 25 g batch of capsules exposed to flue gas conditions in a fluidized column. This model is then scaled up to represent two absorber designs: a multi-stage, counter-flow fluidized bed and a hollow, cylindrical packed bed with radial gas flow. These two absorber bed models are first optimized for a 1 MWe pilot-scale absorber, and then optimized for a 500 MWe coal plant. This model predicts absorbers of similar dimensions and smaller energy penalties than previously modeled absorbers filled with amine solvent capsules. Furthermore, it is demonstrated here that a few reasonable improvements to capsule design would result in absorber sizes and energy penalties lower than those of a benchmark amine solvent tower. These results demonstrate that micro-encapsulated carbonate solution can compete with faster-acting amine solvents for post-combustion carbon capture.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition

Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the pilot-scale model, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. The ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. Here this method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about 15–40 times faster with only ~1% relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A Geostatistical Study in Support of CO 2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China

The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 ton-per-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena observed during 3 years of Shenhua CCS operations. Although there was a brief period of wellhead pressure increase at the injection well, it unexpectedly dropped for most of the time. Another interesting observation showed that the majority of CO 2 gas injection was received by the topmost sandstone Liujiagou formation instead of the basement limestone Majiagou formation, which was predicted to have much more injectivity and storage capacity. Based on the current geostatistical methods and available data, 3 steps of reservoir modeling and flow simulation are carried out and they go from having homogeneous property models to incorporating standard 2-point geostatistical methods to using object-based models. The layer-cake models generate a rather uniform plume shape and increased pressure response. Meanwhile, two-point statistical models add more complexity to the size and shape of CO 2 plume, however are not capable of reproducing the pressure decline behavior. These results demonstrate homogeneous and 2-point geostatistical models are inadequate in interpreting subsurface heterogeneity, both due to their method and data limitations. Further work is being done with object-based models to produce a system of meandering rivers based on the geological concept of Shenhua injection site. This will help offset the data limitation and bring our model closer to geologic reality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling the First Hydrogen Direct Reduction Pilot Reactor for Ironmaking in the USA Using Finite Element Analysis and Its Validation Using Pilot Plant Trial Data

Direct reduction of hematite pellets with hydrogen (H 2 ) was used to produce directly reduced iron (DRI) in a pilot scale reactor at a pellet feed rate of 21.4 kg/h. At a steady state, operational parameters of the pilot plant (gas recycling rate and inlet temperature) along with key reactor output parameters, the pellet metallization, and the internal temperature profile of the reactor were reported for two scenarios with high recycle and low recycle rate of H 2 . Scenario 1, with a high recycle rate of 400 L/min H 2 along with external heating of 870 °C, gave an average metallization of 91.8%, while Scenario 2, with low recycle rate of 100 L/min H 2 and external heating of 850 °C gave a metallization of 67.8% due to the higher moles of H 2 available for reduction and the external energy required for the endothermic reduction reaction in Scenario 1 as compared with Scenario 2. Finite element analysis was used to build a model of the shaft reactor, which was validated against the metallization and internal temperature profile data. The average metallization values predicted by the model were very close to the metallization values obtained from the pilot plant samples, with 90.9% average metallization for Scenario 1 and 65.6% average metallization for Scenario 2. The internal temperature profiles in the lower region of the reactor obtained from the model were very close to these pilot plant data, with a maximum difference of 52.7 °C and 67.6 °C for Scenarios 1 and 2, respectively. The pilot plant reactor model was used extensively in the commissioning of the pilot plant and to predict the startup outcomes for a given set of operating parameters.

08 HYDROGEN↗
DOE OSTI2026

Bike and Scoot to Transit

In this project, we developed a micromobility first-mile service for customers to access public transit. We launched this service as a pilot in the Seattle area that incentivized transit customers to bike or scoot to transit. The objective was to learn how to integrate different micromobility services and provide a unified reward program. Our pilot was called “Bike and Scoot to Transit” and ran from November 2022 to September 2023. More than a dozen locations were selected near transit hubs and light rail/train stations as preferred parking locations. Trips ending at those locations were partially funded. The pilot supported 19,226 qualified trips and distributed $73,000 in total benefits for the participants of the pilot. This dataset was collected from our pilot, which includes the following: - Monthly data: Monthly trip and funding summaries. - Data summary: Data broken down based on the micromobility service provider and equipment. - Trip data: List of all trips recorded during the pilot. - Pricing models: Fees charged by micromobility service providers. ![bike to transit](bike-transit.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Model calibration and optimization of a post-combustion CO 2 WAG pilot in a mature oil field

A carbon dioxide (CO 2 ) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO 2 flood in the West Ranch Field as part of the Petra Nova project, the world's largest postcombustion CO 2 capture and utilization initiative. With a fluvial formation geology, this is a challenging and novel application of CO 2 enhanced oil recovery. The aim of this study is two-fold. First, to build a predictive dynamic model that incorporates the data acquired during the pilot operation. Second, to utilize this model to provide guidance for optimal design for a field-wide CO 2 EOR operation. Our study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. Next, local permeability field is fine-tuned using a streamline-based method to match CO 2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO 2 recovery as a fraction of the injected CO 2 . Sensitivity studies were conducted using the calibrated pilot model to evaluate the effects of various operational parameters. Finally, we performed a Design of Experiment based multi-objective optimization of the CO 2 WAG processes using the influential operational parameters identified from the sensitivity analysis.

02 PETROLEUM↗
DOE OSTI2020

Digital Biosecurity Pilot Project

Security models for the bioeconomy have largely been developed on risk profiles borrowed from the financial industry and, in some cases, industrial control systems. The bioeconomy, however, has unique characteristics that require domain-specific knowledge of the risks to environmental, health and economic impact from directly targeted attacks. Key questions need to be assessed and answered for any facility engaged in bioproduction. These include: how much technical information must the attacker possess in order to target a specific process or facility? Which processes cause the largest economic impact if disrupted? Can an attacker lead companies down the wrong path of research, leading to irrecoverable losses of time, resources and capital? Can attackers disrupt venture capital strategies and affect financial returns? What are the resources required to attack key workflows, and subsequently what is the cost of defense? What strategies are effective against such attackers, and what are their cost? Can government provide an active role in assurance of material, process and results for critical bioeconomic infrastructure?

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
DOE OSTI2018

Techno-Economic Evaluation of Cellulosic Ethanol Production Based on Pilot Biorefinery Data: a Case Study of Sweet Sorghum Bagasse Processed via L+SScF

Replacing fossil fuels with renewable fuels derived from lignocellulosic biomass can contribute to the mitigation of global warming and the economic development of rural communities. This will require lignocellulosic biofuels to become price competitive with fossil fuels. Techno-economic analyses can provide insights into which parts of the biofuel production process need to be optimized to reduce cost or energy use. Here, we used data obtained from a pilot biorefinery to model a commercial-scale biorefinery that processes lignocellulosic biomass to ethanol, with a focus on the minimum ethanol selling price (MESP). The process utilizes a phosphoric acid-catalyzed pre-treatment of sweet sorghum bagasse followed by liquefaction and simultaneous saccharification and co-fermentation (L+SScF) of hexose and pentose sugars by an engineered Escherichia coli strain. After validating a techno-economic model developed with the SuperPro Designer software for the conversion of sugarcane bagasse to ethanol by comparing it to a published Aspen Plus model, six different scenarios were modeled for sweet sorghum bagasse Under the most optimistic scenario, the ethanol can be produced at a cost close to the energy-equivalent price of gasoline. Aside from an increase in the price of gasoline, the gap between ethanol and gasoline prices could also be bridged by either a decrease in the cost of cellulolytic enzymes or development of value-added products from lignin.

Biofuel↗
DOE OSTI2026

First Wall Design of a Tokamak Pilot Plant Using a Monte Carlo Model for 3-D Heat Flux Deposition

We present a method for calculating the heat fluxes deposited on nonaxisymmetric tokamak first wall components, allowing for a first-of-its-kind model for power handling in the tokamak far scrape-off layer (SOL). The DIV3D Monte Carlo model features strict global power conservation and can calculate the finite cross-field plasma transport into magnetically-shadowed regions, which is significant when dealing with meter-scale shadows introduced by components such as poloidal limiters or antennas. As a case study, we apply the DIV3D model to inform the distribution of first wall poloidal limiters in an ARC-class reactor device. We demonstrate that discrete protection limiters can efficiently reduce peak heat fluxes on recessed breeder wall components in the presence of significant far-SOL plasma fluxes. By varying the toroidal periodicity and radial standoff depth of the limiters, we demonstrate one of the tradeoffs that must be considered in first wall design: more limiters provide greater protection, but at the cost of reduced breeding performance. We also present the impact that radial misalignments between limiters would have on first wall power loading.

Monte Carlo methods↗
DOE OSTI2024

Model-Based Sequential Design of Experiments for Pilot Testing of Novel Water-Lean CO2 Capture Solvent

Poster for the 2024 Fossil Energy and Carbon Management Meeting. It summarizes work done on process modeling and uncertainty quantification in preparation for the test campaign at the National Carbon Capture Center for a general audience. The poster includes sections detailing background on the EEMPA solvent, sequential design of experiments, process modeling (including results from the model), uncertainty quantification, and the goals of the test campaign.

Hedrick, Katherine↗
DOE OSTI2020

A Handbook for Designing, Implementing, and Evaluating Successful Electric Utility Pilots

Since at least the late 1970s, electric utilities and their regulators have recognized the value of experimentation to motivate innovation. The industry has a long history of using pilots to help inform future decision making about electric utility rates, customer technology adoption and integration, and even changes to the utility’s regulatory or business model. Although utility pilots have become almost ubiquitous proving grounds for new rates, technologies, and alterations to the traditional utility regulatory and business model, some regulators are beginning to raise questions about what constitutes a “good” pilot. Much has been written about utility pilots over the years; however, what is missing from the literature is the identification of a comprehensive process for not only designing and evaluating a pilot, but also implementing, successful utility pilots that provide actionable outcomes upon which more informed decisions can be made. This report provides a step-by-step process that regulators, policymakers, and utilities can follow to help promote a more successful pilot, even if whatever is being tested fails to produce the intended or expected result(s). It is worth noting that this report is not intended to serve as a technical resource for those designing, implementing, and evaluating pilots. However, there are myriad references provided for those wishing to delve deeper into the technical details.

24 POWER TRANSMISSION AND DISTRIBUTION↗