Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Pilot Inputs”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tailoring Cementitious Materials Towards Value-Added Use of Large CO 2 Volumes

Hydraulic cements with alternative chemistries were developed for large-volume and value-added use of carbon dioxide. The hydraulic cements were processed using the energy-efficient mechanochemical technique at room temperature and atmospheric pressure. Carbon dioxide was captured directly from combustion emissions during processing. For this purpose, mechanochemical processing of hydraulic cements was accomplished under a flow of combustion emissions prior to the release of emissions to the atmosphere. The process removed a significant fraction of carbon dioxide from combustion emissions. The hydraulic cements captured carbon dioxide at about 10% of their weight. Two hydraulic cement chemistries were developed, and their mechanochemical processing was successfully scaled-up. The characteristic feature of one chemistry was its relatively low (near-neutral) pH where the integration of carbon dioxide yielded clear value. The second cement chemistry was based on alkali activation of industrial wastes. This chemistry could make value-added use of carbon dioxide, but it had to be refined to control the pH drop caused by CO 2 integration. These two cements render binding effects upon hydration by forming a combination of stable carbonates and aluminosilicates or phosphates. Efforts to develop cement chemistries based solely on carbonates were not successful. The mechanochemical process was found to integrate carbon dioxide into the alternative cement chemistries in the form of disordered and metastable carbonates. During hydration reactions, the disordered/metastable carbonates are either transformed into stable carbonate phases with desired binding efforts, or carbonates get integrated into the primary inorganic binders (hydrates). When compared with mechanochemical processing in pure carbon dioxide, mechanochemical processing in combustion emissions produced hydraulic cements with improved engineering properties. The mechanochemical process was scaled-up, and its variables as well as the raw materials formulations were optimized for implementation at pilot scale. Scale-up was found to enhance the carbon capture potential and the engineering qualities of the resulting hydraulic cements. This was because scale-up raises the intensity of mechanical energy input to raw materials. Certain mechanochemical phenomena cannot be induced, irrespective of the cumulative mechanical energy input, unless the intensity of impact is raised above a minimum level that cannot be achieved in laboratory-scale implementation of the process. Due to this effect, the duration of the mechanochemical process as well as its energy demand could be reduced significantly (by an order of magnitude) upon transition from laboratory to pilot scale, with the hydraulic cements produced at pilot scale offering engineering properties that were superior to those realized in laboratory-scale mechanochemical processing. The hydraulic cements produced at pilot scale via mechanochemical processing under a flow of combustion emissions were thoroughly characterized. They were found to meet standard requirements for ‘General Use’ hydraulic cements. They were compatible with the industrial-scale concrete production and construction practices that are used with the currently prevalent hydraulic cements. The new hydraulic cements with integrated carbon dioxide were found to offer distinct advantages over the currently prevalent Portland cement in terms of net carbon footprint and energy content. The combined raw materials and energy costs of the new hydraulic cements are competitive, and major cost savings can be realized because of the simplified production process that significantly lowers the capital investment in cement production plants. Mechanochemical processing of the new hydraulic cements under a flow of combustion emissions can be implemented using some existing components of cement manufacturing plants; this facilitates adoption of the technology by the cement industry.

36 MATERIALS SCIENCE↗
DOE OSTI2022

SolarAPP+ Pilot Analysis: Performance and Impact of Instant, Online Solar Permitting

The National Renewable Energy Laboratory (NREL) led a collaborative effort to develop the Solar Automated Permit Processing Plus (SolarAPP+), a no-cost solar permitting software solution to address residential solar photovoltaic (PV) permitting resource constraints and streamline solar adoption processes among authorities having jurisdiction (AHJs). The SolarAPP+ is an online portal that automates permit plan review, enabling an instant permit approval process for code-compliant residential PV systems. Based on national model building, electrical, and fire codes, the SolarAPP+ automatically performs a compliance check of permit inputs against code requirements and produces an inspection checklist that can be used to verify installation practices, workmanship, and adherence to the approved design. NREL conducted a two-phase pilot with five participating AHJs and 16 solar contractors, spanning from November 2020 through December 2021, evaluating the ability of SolarAPP+ to deliver instant permits and its impact on four critical areas within each AHJ: permit review timelines; solar adoption timelines; AHJ time saved; and inspection results. The pilot confirmed that SolarAPP+ reduced permit review times to less than one day, reduced solar adoption timelines by an average of 12 days, saved an estimated 2,067 staff hours, and had comparable inspection results to those found in traditional permitting. The pilot further identified key lessons for improving SolarAPP+, including ways to streamline SolarAPP+ adoption, development of training resources, and expansion of supported products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Estimation of pipe failure frequencies in the absence of operational experience data: A pilot study

Probabilistic failure metrics such as leak frequency and rupture frequency are commonly used to characterize piping reliability. The methodologies for calculating the failure metrics rely on a complex set of input parameters. Operating experience data and experimental data play an important role in informing the different input parameters. The paper describes results and conclusions of a coordinated research project to benchmark three different reliability models using a four-step procedure: reference case definition of relevance to advanced reactor designs, input parameter calibration, validation of results, and application of different methodologies upon completion of the calibration and validation steps. The reference case is a weld consisting of nickel-base alloy 152/52 and located within a primary pressure boundary of an advanced reactor. This alloy is a class of structural materials known to be highly resistant to stress corrosion cracking. Synergies between the different methods are noted and the importance of a multi-disciplinary approach to input parameter development is underscored. A key conclusion is that the three methods are equally suitable for estimating failure frequencies. In any specific application, a selection of the most practical or effective computational tool can be considered. The comparison of alternative models confirms and helps to gain confidence in the computed failure frequency estimates. The study was part of a coordinated research project organized by the International Atomic Energy Agency.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Annual Transuranic Waste Inventory Report – 2020 (Data Cutoff Date 12/31/2019)

The purpose of this Annual Transuranic Waste Inventory Report (ATWIR) – 2020 is to document the inventory estimate of transuranic (TRU) waste reported by the TRU waste generator sites as of December 31, 2019. This report also notes major changes to the inventory used for the ATWIR-2019 that had a data cutoff date of December 31, 2018. This updated inventory information is available to the U.S. Department of Energy (DOE) TRU waste complex, Waste Isolation Pilot Plant (WIPP) stakeholders, and regulators. The TRU waste inventory information is used for strategic planning, and supports the DOE Carlsbad Field Office (CBFO) input into documents (e.g., WIPP Documented Safety Analysis and National Environmental Policy Act analyses), planned changes, and other design changes as needed for the WIPP project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Annual Transuranic Waste Inventory Report – 2021 (Data Cutoff Date 12/31/2020)

The purpose of this Annual Transuranic Waste Inventory Report (ATWIR) – 2021 is to document the inventory estimate of transuranic (TRU) waste reported by the TRU waste generator sites as of December 31, 2020. This report also notes major changes to the inventory used for the ATWIR-2020 that had a data cutoff date of December 31, 2019. This updated inventory information is available to the U.S. Department of Energy (DOE) TRU waste complex, Waste Isolation Pilot Plant (WIPP) stakeholders, and regulators. The TRU waste inventory information is used for strategic planning, and supports the DOE Carlsbad Field Office (CBFO) input into documents (e.g., WIPP Documented Safety Analysis and National Environmental Policy Act analyses), planned changes, and other design changes as needed for the WIPP project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Annual Transuranic Waste Inventory Report – 2022 (Data Cutoff Date 12/31/2021)

The purpose of this Annual Transuranic Waste Inventory Report (ATWIR) – 2022 is to document the inventory estimate of transuranic (TRU) waste reported by the TRU waste generator sites as of December 31, 2021. This report also notes major changes to the inventory since the ATWIR-2021, which had a data cutoff date of December 31, 2020. This updated inventory information is available to the U.S. Department of Energy (DOE) TRU waste complex, Waste Isolation Pilot Plant (WIPP) stakeholders, and regulators. The TRU waste inventory information is used for strategic planning, and supports the DOE Carlsbad Field Office (CBFO) input into documents (e.g., WIPP Documented Safety Analysis and National Environmental Policy Act evaluations), performance assessments, planned changes, and other design changes as needed for the WIPP project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Model predictive combustion control of a Gasoline Compression Ignition engine

Gasoline Compression Ignition is a novel combustion concept that derives its superiority from the high compression ratio of a compression ignition engine as well as the properties of gasoline fuel, such as longer ignition delay and higher volatility compared to diesel. Here, this combustion concept was experimentally tested on a 12.4L Class 8 truck engine. Based on these experimental data, prior efforts by the authors focused on the development of an engine model for a heavy-duty engine operating on a low-reactivity fuel. This engine model was leveraged within this study to investigate a combustion control strategy at different engine conditions and injection methods and was augmented to incorporate cycle-to-cycle combustion variations. State estimation is performed by means of a Kalman filter which feeds into a model predictive controller. The model predictive controller chooses control actions based on a predefined cost function under consideration of bounds reflecting physical constraints. The engine model was utilized to establish a state-space model that serves the Kalman filter and model predictive controller for estimation and prediction. A comparative study investigating control actions and engine behavior was performed with and without limiting in-cylinder peak pressure as well as combustion noise, which is of particular interest for early pilot injection strategies. In addition, the proposed control architecture was investigated at two different levels of cycle-to-cycle variations and compared to the performance of a control structure with input disturbance rejection. For increased cycle-to-cycle variations, disturbance estimation reduces state fluctuations and control effort. In general, this investigation highlights control aspects specific to a compression-ignited combustion regime with low-reactivity fuel. The control algorithm is able to maintain the desired references for brake mean effective pressure and combustion phasing while controlling peak in-cylinder pressure and combustion noise.

42 ENGINEERING↗
DOE OSTI2022

The SMART Cables Initiative for Ocean and Geophysical Observing [Slides]

SMART Cables are becoming a reality, and have the potential to revolutionize submarine oceanographic and geophysical sensing. Pilot / demonstration projects are underway to test the technology and explore the feasibility of incorporating both in-repeater standardized sensor packets but also ancillary sensor types on external, branching nodes. The projects currently in planning will set the standard and influence the norms for the future of SMART systems. The interest of all potential stakeholders and users, and input as to needs and concerns, is welcomed as testing proceeds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Treatment of brackish water reverse osmosis brine using only solar energy

Post-treatment of brine produced by reverse osmosis (RO) is a great challenge as it often requires high energy input and works under extreme operating conditions. In this study, brine from a RO plant in El Paso, TX USA was successfully treated using a pilot-scale nanophotonics enhanced solar membrane distillation (NESMD) system. The novel NESMD reactor has a nanophotonic membrane surface area of 0.2 m 2 and an internal heat recovery system to recover the latent heat released during vapor condensation. By utilizing a sweeping gas operational mode under real solar irradiation (585–827 W m -2 ), the NESMD realized successful desalination of RO brine with the membrane flux reaching 0.45–0.65 kg m -2 h -1 and total dissolved solids (TDS) removal greater than 99.5% without an external heat condenser. The decrease in the feed flow rate to the evaporation channel of the NESMD system led to an increase in the gained output ratio (GOR) from 0.35 to 0.62. We report to the best of our knowledge, this is the largest photothermal reactor utilized for the desalination of real RO brine under practical solar irradiation. Compared with conventional brine treatment processes that require high temperature or pressure, the NESMD desalinates RO brine at near-ambient temperature and pressure with free solar energy, providing a promising approach for water desalination, and RO brine post treatment.

42 ENGINEERING↗
DOE OSTI2021

Aerosol–Ice Formation Closure: A Southern Great Plains Field Campaign

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. Furthermore, the closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

58 GEOSCIENCES↗
DOE OSTI2024

Modeling Approach for the Aluminum-clad Dry Storage Pilot using HFIR Fuel

To confirm that the dry storage of aluminum-clad research reactor spent nuclear fuel (ASNF) will remain within the safety envelope after applied drying schemes and that the resulting evolution of the gas space composition, temperature, and pressure conditions are understood, a dry storage pilot project is being established. The pilot will incorporate an instrumented lid for discrete interval or for on-demand gas composition and temperature monitoring of two DOE Standard Canisters (DSCs) loaded with three High Flux Isotope Reactor (HFIR) inner cores per DSC. Each DSC would be subjected to a separate alternative candidate drying scheme. Canisters will undergo 1 to 5 years of monitoring, including internal temperature and gas sampling to track pressure and composition changes. This report outlines the approach for modeling the ASNF-in-canister behavior in terms of evolving gas space conditions for the ASNF dry storage pilot using HFIR fuel. The ASNF has an adherent surface oxyhydroxide layer comprised of boehmite/bayerite that generates hydrogen when subjected to irradiation. Three-dimensional multi-physics computational fluid dynamics simulations will be executed to compute the thermal field within the DSC and provide inputs to a chemical model employed to compute pressure buildup as hydrogen is generated in the system. Implemented in Cantera, the chemical model solves gas phase and aluminum oxyhydroxide surface-mediated radiolysis reactions. Gas phase reactions are sourced from Wittman and Hanson (2015), whereas surface-mediated reactions are incorporated by fitting experimental data using an optimization algorithm (Abboud, 2023). Water radiolysis reactions from Wren and Ball (2001) are adopted with modifications as described in Abboud (2023c). Understanding the effect of the hydrogen buildup over time is important for long-term storage safety considerations. Modeling results will include the canister pressure, temperature, and composition evolution from the initial helium backfill with the addition of radiolytically-evolved chemical species (e.g., hydrogen and oxygen). The specific HFIR cores for the pilot program have not yet been selected, and the overall design is still in development. The CFD-chemical model used for this work will be based on prior models with necessary updates to allow for improved accuracy and efficiency. The experimental data obtained from the HFIR demonstration will be used to improve and validate the computational models to predict the ASNF-in-canister behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Final Report for FE0032098: Improving the cost-effectiveness of algal CO2 utilization by synergistic integration with power plant and wastewater treatment operations

The overall goal of this project was to demonstrate an engineering-scale open raceway pond algae cultivation system (approximately 180 m²), including the integration of technologies that utilized carbon dioxide (CO₂) from a coal-fired power plant and wastewater-derived nutrient inputs for cost-effective and environmentally friendly biomass production. The key advantages associated with the innovative algae cultivation system and its integration with wastewater treatment functions, as described herein, had been demonstrated in previous bench- and pilot-scale work by the project team partners. This project combined those approaches to maximize practical benefits and available synergies, resulting in a significant reduction in the net cost of producing algal biomass products. The primary target algal species for the project was Spirulina, which served as a high-protein content ingredient for food and animal feed. Spirulina was selected because it had already been approved by the FDA, was in use as a food ingredient, and commanded prices of up to $30/kg. It had a typical protein content of 50–75%, comparable to other high-protein concentrates, featured high digestibility without requiring pretreatment, and offered a high conversion ratio in animal feed applications. In addition, Spirulina had a relatively high content of the blue pigment phycocyanin, which could be extracted as a high-value co-product prior to using the remaining biomass for nutritional purposes.

Schideman, Lance [University of Illinois]↗
DOE OSTI2023

Adaptively Learned Modeling for a Digital Twin of Hydropower Turbines with Application to a Pilot Testing System

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

13 HYDRO ENERGY↗
DOE OSTI2023

Verification Testing of OLI Systems Mixed Solvent Electrolyte Model for the Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 ) System to High Ionic Strength at 25°C

This technical report summarizes model verification results and summary statistics for 41 evaporite mineral solubility cases evaluated by Savannah River National Laboratory using OLI Systems’ aqueous electrolyte thermodynamic modeling software. The 41 verification cases containing a total of 60 solubility curves comprise mineral solubility data from low to high ionic strength at 25°C for the eight-component system Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 O as reported by Harvie et al. (1984). Thermodynamic calculations were executed using OLI Systems’ Stream Analyzer computation module within the OLI Studio software platform (Ver. 11.0, Rev. 11.0.1.9). The Mixed Solvent Electrolyte (MSE) thermodynamic framework was chosen for this investigation because of its superiority in modeling high ionic-strength inorganic salt solutions and actinide redox chemistry and solubility, both of which are relevant to the geological repository conditions at the Waste Isolation Pilot Plant in Carlsbad, New Mexico. Mineral solubility data in various inorganic salt solutions were digitized and extracted from figures generated by Harvie et al. (1984). For each of the 60 solubility curves, a case-specific chemistry model and input file were generated in OLI Studio using OLI Stream Analyzer and the MSE (H 3 O + ion) public databank provided by OLI Systems. Model simulation results were exported to Microsoft Excel to calculate summary statistics and to generate graphs comparing the OLI model predictions to the solubility data. Summary statistics include residuals (model – data) and concordance (accuracy × precision, where precision is indicated by the Pearson correlation coefficient and accuracy accounts for bias and scale differential). Private databanks were not developed, and activity coefficient model regressions were not performed to improve OLI model fits to the data. Of the 41 model verification plots, 83% have a mean of the percent residuals less than or equal to 25%. Similarly, 75% display a concordance greater than or equal to 0.75. Only seven of the 41 verification plots fail to show good agreement between the model and data. Of these seven, three are relevant to the WIPP repository because they involve the Mg-OH-Cl-SO 4 -CO 3 aqueous system. The remaining four address salt solubilities at the pH extremes (strong acid and strong base). It should be noted that in two of the three Mg-OH-Cl-SO 4 -CO 3 system cases, the regressed Harvie et al. (1984) solubility curve also deviated from the data. Lack of agreement between the OLI model-predicted solubility curves and the data is attributable to one or more of the following: specific solid species are not included in the OLI MSE databank; there is significant variation among the different solubility datasets chosen by Harvie et al. (1984); the OLI MSE model’s thermodynamic parameters were determined using different solubility datasets; and the activity coefficient parameters for certain relevant ion-ion and ion-molecule pairs have not been optimized via data regression. Two recommendations for future work are to (1) evaluate solubility data for the Mg-OH-Cl-SO 4 -CO 3 system at high ionic strength and, if necessary, develop a private OLI MSE database that includes missing species and, where necessary, regressed standard state properties and interaction parameters; (2) perform similar verification testing of the OLI model for actinide solubility data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Simulations of Criticality Control Overpack Container Compaction at the Waste Isolation Pilot Plant

Criticality Control Overpack (CCO) containers are being considered for the disposal of defense-related nuclear waste at the Waste Isolation Pilot Plant (WIPP). At WIPP, these containers would be placed in underground disposal rooms, which will naturally close and compact the containers closer to one another over several centuries. This report details simulations to predict the final container configuration as an input to nuclear criticality assessments. Each container was discretely modeled, including the plywood and stainless steel pipe inside the 55-gallon drum, in order to capture its complex mechanical behavior. Although these high-fidelity simulations were computationally intensive, several different material models were considered in an attempt to reasonably bound the horizontal and vertical compaction percentages. When exceptionally strong materials were used for the containers, the horizontal and vertical closure respectively stabilized at 43:9 % and 93:7 %. At the other extreme, when the containers completely degraded and the clay seams between the salt layers were glued, the horizontal and vertical closure reached respective final values of 48:6 % and 100 %.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Development of a Modular, Crushed-Rock Thermal Energy Storage Pilot Design

The goal of this project, primarily funded by the U.S. Department of Energy, is to design a next-step pilot to advance near-term energy storage integrated with a fossil plant to provide a facility capable of being viable and effective in a market with growing penetration of variable renewable energy (VRE). Thermal energy storage (TES) represents an ideal technology for this purpose. The current effort will complete a feasibility study to prepare for the Phase II pre-front end engineering design (pre-FEED) for implementing a crushed-rock TES system integrated with a natural gas combined cycle (NGCC) plant. The crushed rock storage technology, which is being developed by Brenmiller Energy, is a modular TES system termed bGen™, which can accommodate both thermal and electrical inputs and output steam, hot water, or hot air. For this application, the estimated efficiency is 80% thermal to thermal. The TES technology is being designed to operate on a slipstream from NYPA’s Eugene W. Zeltmann Power Project (Zeltmann) natural gas combined cycle (NGCC) plant. The projected size of the system will be up to 4 MWe with at least 4 hours of storage duration, or 16 MWh-e total. Final sizing is being determined during the ongoing feasibility study. The next-step pilot being designed as part of the current project will represent a 5-fold increase in scale for this TES technology, and will be used to validate the technology’s ability to provide effective and economical energy storage. This pilot would represent the next-to-last demonstration scale before the technology could be commercial ready at GWh-e scales in the 2030 timeframe. This project is expected to design the critical next-step pilot, which will be undertaken in real-world operating conditions to better determine the crushed rock TES technology’s ability to be integrated with an NGCC plant and assess degradation over transient cycling at rates befitting various marketplaces. The crushed-rock TES pilot design is a technically feasible next step in the development of the technology and is built upon years of prior testing and demonstration. The proposed TES technology was developed by Brenmiller over the last 8 years and has been tested in 3 generations of demonstration units at various sites, globally. During this field testing, different characteristics and performance of the technology were validated, including the following key features: energy storage capacity, energy storage charge/discharge rate, energy storage loses, energy storage mechanical testing. This presentation will provide an update on the results of the conceptual design study for the modular crushed-rock TES system, integrated with a NGCC power plant.

03 NATURAL GAS↗
DOE OSTI2021

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗