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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 145 records · Page 8

PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) comprehensively analyzes possible pathways for Puerto Rico to achieve its renewable energy goals while incorporating stakeholder perspectives and advancing energy resilience for all Puerto Ricans. PR100 is a wide-ranging and in-depth examination of Puerto Rico's energy system investment options. The findings are the culmination of two years of stakeholder engagement, scenario modeling, and impact analysis. The PR100 report and Implementation Roadmap contain a range of results and actions that reflect Puerto Rico's priorities around energy justice, resilience, and reliability. Led by the U.S. Department of Energy's Grid Deployment Office with funding from the Federal Emergency Management Agency, the PR100 study leveraged and integrated dozens of best-in-class models and in-depth analyses from researchers across six national laboratories: National Renewable Energy Laboratory (which led the study), along with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories (which conducted the study). For more information, please see the "PR100 Project Website" resource below.

Array↗

Expanded Validation of Uranium Systems with the KENO Monte Carlo Codes and SCALE 6.2.4

The development of accident-tolerant fuel and advanced reactors fueled with high-assay low-enriched uranium has created an increased focus on systems with uranium enrichments between 5 and 20 wt % 235 U. SCALE criticality safety validation reports generated at Oak Ridge National Laboratory contain very few benchmark experiments in this range. The work presented herein is an initial investigation of expanded validation of the entire range of enrichments for uranium-fueled systems, including consideration of over 300 newly developed KENO models. The vast majority of the new models are between 4.4 wt % and 37.5 wt % enrichment and include a variety of thermal, intermediate, and mixed neutron spectra. This work finds no strong evidence of an enrichment-dependent bias, but there are indications of a spectrum-dependent bias. There are, however, only a limited number of independent experiments included at this time to distinguish intermediate enrichment effects from intermediate spectrum effects. Further work in this area is ongoing for intermediate enrichment systems. In the long run, the addition of these models to the Verified, Archived Library and Inputs and Data is planned, as funding and staff availability allow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Conference Support for CU*IP at UCONN

This award supported six students to attend the national Conference for Undergraduate Women and Gender Minorities in Physics (CU*IP) held at the University of Connecticut on January 24-26, 2025. The CU*IP conference series provides opportunities for under-represented undergraduate students to obtain real conference experience, hear from role models in the field of physics, and to network with their peers. The funds will support travel, lodging, and meal expenses for students otherwise not able to attend the meeting.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗

Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers

We report sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy’s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining “range-finder” dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.

54 ENVIRONMENTAL SCIENCES↗

ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]

ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.

Horsey, Henry↗

Supporting Bioproducts Industry Growth with a System Dynamics Decision-Support Tool

A bio-based economy requires chemical products as well as fuels to be produced from biomass. Although a variety of universities, government agencies, start-ups and established firms have engaged in bioproduct development, many projects have failed to reach the point of commercialization and commercialized bioproducts struggle to capture and maintain market share. To date, there has been no general research into the factors that contribute to bioproduct failure or success. This work presents the Bioproduct Transition Dynamics (BTD) system dynamics model, a decision-support tool that simulates the bioproduct development process from pre-piloting research through construction of the first commercial-scale plant, as well as the processes of obtaining funding from investors and government agencies. The core of the BTD is a feedback loop between bioproduct developers and funders, which relates development progress measured with indicators such as net present value to funders’ decisions to continue investing. External factors such as feedstock prices, market size and growth, and the existence of bioproduct consumers also influence a development project’s chances of receiving follow-on funding. Virtually any bioproduct can be represented with the BTD: direct replacements, performance-advantaged products, niche and commodity markets can all be modeled. The goal of the BTD project is to inform decisions made by developers in both established firms and start-ups, investors, government agencies, and other stakeholders interested in growing the nascent U.S. bioproducts industry. This talk will cover the general structure and functionality of the BTD, and present results from an analysis performed with the BTD to demonstrate its use as a decision-support tool and the insights it can provide. The goal of the analysis is to identify the most critical factors that lead to direct replacement and performance-advantaged bioproduct projects emerging successfully from the “Valley of Death”, and to determine if these factors differ between the two bioproduct types.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

In support of DOE's H2@Scale initiative, this project leverages with national lab capabilities at SNL, NREL, and ANL with collaboration and funding cost share from California agencies (CEC, South Coast AQMD, and GO-Biz) to enable the build-out of heavy-duty (HD) hydrogen fueling stations with large dispensing capacity and high flow rates by providing tools and information that lead to more efficient design, acceptance, and commissioning. In this presentation, we describe the progress as related to the subtasks of: HD Reference Station Design, HD Station Test Device Design, and the Station Capacity Model.

AMR↗

Bioscience COVID Rapid Response Report

The COVID-19 disease outbreak and its impact on global health and economies have highlighted the national security threat posed by pathogens with pandemic potential and the need for rapid development of effective diagnostics and medical countermeasures. The Bioscience IA selected for funding rapid COVID LDRD project proposals that addressed critical R&D gaps in pandemic response that could be accomplished in 1-3 months with the requested funding. In total, the Bioscience IA funded nine rapid projects that addressed 1) rapid and accurate methods for SARS-CoV-2 RNA detection, 2) modeling tools to help prioritize populations for diagnostic testing, 3) bioinformatic tools to track SARS-CoV-2 genomic sequence changes over time, 4) molecular inhibitors of SARS-CoV-2 cellular infection, and 5) method for rapid staging of COVID19 disease to enable administration of more effective treatments. In addition, LDRD funded one larger project to be completed in FY21 that leverages Sandia capabilities to address the need for platform diagnostics and therapeutics that can be rapidly tailored against emerging pathogen targets.

59 BASIC BIOLOGICAL SCIENCES↗

Pre-Ionization Controlled Laser Plasma Formation for Ignition Applications (Final Scientific/Technical Report)

This report consists of three grand funded papers. Abstracts for each follow. 1) In this work, we present experimental and modeling studies of air pre-ionization using ultraviolet (UV) laser pulses and its effect on laser breakdown of an overlapped near-infrared (NIR) pulse. Experimental studies are conducted with a 266 nm beam (fourth harmonic of Nd:YAG) for UV pre-ionization and an overlapped 1064 nm NIR beam (fundamental of Nd:YAG), both having pulse duration of 10 ns. Results show that the UV beam produces a pre-ionized volume which assists in breakdown of the NIR beam, leading to reduction in NIR breakdown threshold by factor of >2. Numerical modeling is performed to examine the ionization and breakdown of both beams. The modeled breakdown threshold of the NIR, including assist by pre-ionization, is in reasonable agreement with the experimental results. 2) The present contribution compares the energy absorption, optical emission, temperature, and fluid dynamics of ultraviolet (UV) λ = 266 nm and near infrared (NIR) λ = 1064 nm nanosecond laser induced plasmas in ambient air. For UV pulses at the conditions studied, energy absorption by the plasmas increases relatively gradually with laser pulse energy starting at delivered energy of E~8 mJ. Corresponding measurements of plasma luminosity show that the absorption of UV radiation does not necessarily result in visible plasma emission. For the NIR induced plasmas, the energy absorption profile is far more abrupt and begins at ~55 mJ. In contrast with UV, the absorption of NIR radiation is always accompanied by intense optical emission. The temperatures of both types of plasma have been measured with Rayleigh scattering thermometry (at times after the Thomson signal sufficiently diminishes). The UV plasmas can attain a wider range of temperatures, including lower temperatures, depending on the pulse energy (e.g., T ~400–2000K for E ~7–35 mJ at Δt = 10 μs after the pulse) while the NIR plasmas show only hotter temperatures (e.g., T ~ 12 000 K for E = 75 mJ at Δt = 10 μs after the pulse) as is consistent with the literature. Differences in the fluid dynamics for UV versus NIR pulses are shown with Schlieren imaging. In this work, the contrast in the UV and NIR plasma threshold behavior is attributed to differing roles of avalanche ionization and multiphoton ionization as is also illustrated by a simple numerical model. 3) The present contribution examines the impact of plasma dynamics and plasma-driven fluid dynamics on the flame growth of laser ignited mixtures and shows that a new dual-pulse scheme can be used to control the kernel formation process in ways that extend the lean ignition limit. We perform a comparative study between (conventional) single-pulse laser ignition (λ = 1064 nm) and a novel dual-pulse method based on combining an ultraviolet (UV) pre-ionization pulse (λ = 266 nm) with an overlapped near-infrared (NIR) energy addition pulse (λ = 1064 nm). We employ OH* chemiluminescence to visualize the evolution of the early flame kernel. For single-pulse laser ignition at lean conditions, the flame kernel separates through third lobe detachment, corresponding to high strain rates that extinguish the flame. In this work, we investigate the capabilities of the dual-pulse to control the plasma-driven fluid dynamics by adjusting the axial offset of the two focal points. In particular, we find there exists a beam waist offset whereby the resulting vorticity suppresses formation of the third lobe, consequently reducing flame stretch. With this approach, we demonstrate that the dual-pulse method enables reduced flame speeds (at early times), an extended lean limit, increased combustion efficiency, and decreased laser energy requirements.

Mechanical engineering↗

Improving GCM Representation of Convective Cloud Microphysics by Using ARM Raman Lidar and Cloud Radar Observations

The overall objective of this Department of Energy (DOE) Atmospheric System Research (ASR) funded project is to improve the representation of convective cloud microphysics in global climate models (GCMs) and check it by comparing the model simulations with observations. We have derived the cloud ice water content by synthesizing ARM Raman lidar (RL) and cloud radar observations at the Atmospheric Radiation Measurement (ARM) sites. Noting that the simulated anvil clouds in terms of their macro- and micro-physical properties are sensitive to the parameterization of convective microphysical processes, observed ice water content in anvil clouds provides a useful constraint on these parameterizations. We have improved the convective microphysics parameterization scheme by (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. We have examined the impact of improved convective cloud microphysics parameterization on the simulated global climate from GCM simulations.

54 ENVIRONMENTAL SCIENCES↗

NEAMS-Multiphysics Technical Assistance in FY21

The Multiphysics Object Oriented Simulation Environment (MOOSE) [1] is a massively parallel finite-element/volume package for multiphysics simulation in science and engineering. The package focuses on providing rapid-development capabilities for engineering applications by leveraging well-built features from libMesh [2] and the Portable Extensible Toolkit for Scientific Computation (PETSc) [3]. Fiscal year 2021 (FY-21) was the first year with funding dedicated to supporting MOOSE-derived applications relevant to the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. In this report we outline the work done to support NEAMS applications such as BISON, Griffin, Pronghorn, and System Analysis Module (SAM).

42 ENGINEERING↗

Thermal Characterization and Exhumation of Northwest San Juan Basin Area, NM

The San Juan Basin (SJB), located in southwestern Colorado northwestern New Mexico, containing Paleozoic through middle Cenozoic strata, formed as a partitioned basin approximately 80 Ma in response to the Laramide orogeny. The SJB is a commercially mature, petroleum-producing basin, and currently being explored for CCUS and geothermal resources. Modern heat flow within the SJB is spatially variable with higher geothermal gradients in its northern and eastern portions. The temporal history of the basin thermal history is essential for understanding capacity for carbon storage and geothermal exploration. We present thermochronometric analyses of two surface and two subsurface samples to constrain spatial-temporal thermal evolution of the northwestern San Juan Basin. Apatite (U-Th)/He thermochronometric analyses were conducted on Cliff House and Kirtland Formation outcrops and subsurface samples of the Ojo Alamo and Pictured Cliffs Formations from a DOE funded, CCUS project pilot-well. In addition, vitrinite reflectance data and 1D basin modelling constrain possible time-temperature pathways of the samples in an area where no previous studies have constrained the uplift/exhumation of the Hogback Monocline using thermochronometry. Modeling suggests that elevated subsurface temperatures developed simultaneously with regional late Oligiocene volcanism in the San Juan Volcanic field and timing of maximum burial in the SJB. Late Miocene to Pliocene cooling/exhumation through the apatite (U-Th)/He partial retention zone support stratigraphic evidence of the Colorado Plateau uplift, possibly regional epeirogenic uplift driven by mantle processes.

02 PETROLEUM↗

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hawai‘i National Marine Renewable Energy Center (HINMREC)

The Hawaii National Marine Renewable Energy Center (HINMREC) was established to facilitate the commercialization of wave energy converter (WEC) devices, and to accelerate development and testing of Ocean Thermal Energy Conversion (OTEC) technologies. Housed at the Hawaii Natural Energy Institute (HNEI) of the University of Hawaii (UH), this program started with execution of the contract between the US Department of Energy (DOE) and UH in March 2009, and activities ran through the end of the project in September 2019. The DOE tasked HINMREC with facilitating and accelerating the build-out of the Navy’s Wave Energy Test Site (WETS), the nation’s first grid-connected open water wave energy conversion test facility, located off Marine Corps Base Hawaii (MCBH) in Kaneohe, on the island of Oahu. WETS was expanded from an existing test berth at 30m water depth to include test berths at 60m and 80m water depths. In recognition of the high costs associated with at-sea testing and evaluation of WEC devices, it was deemed imperative that HINMREC seek ways to reduce costs to developers by providing key research support to these early-stage technologies. WETS and HINMREC’s support allowed development of wave energy technology by providing a testing infrastructure that allows technology developers to test, demonstrate and evaluate their WEC devices, and generate data in order to advance WEC designs toward commercial readiness. HINMREC’s roles have included support in the establishment of the full site, including of wave resource characterization and site survey, followed by the essential roles of independent WEC device power performance assessment and environmental monitoring in support of deployed pre-commercial WECs. This DOE-funded work transitioned effectively to continue Navy-funded tasks for OTEC development, and activities at WETS, now under Naval Facilities Engineering Command (NAVFAC) funding. A secondary objective in the establishment of HINMREC was to assist the private sector in moving OTEC systems beyond proof-of-concept to pre-commercialization, primarily focused on system and component engineering, and local and global investigations into the potential environmental impacts of OTEC systems. HINMREC was tasked with maintaining high-resolution models of ocean thermal resources and the potential sustainable power output of OTEC systems. Ongoing tests begun previously under Navy funding at the OTEC Heat Exchangers (HXs) Test Facility at the Natural Energy Laboratory of Hawaii Authority (NELHA), in Kona on Hawaii Island, have been continued to identify cost-effective aluminum alloys for use in OTEC systems operating in the corrosive marine environment.

16 TIDAL AND WAVE POWER↗

Ferroelectric Large Polarons and Defect Tolerance in Multi-Component Lead Halide Perovskites

Solvation plays a pivotal role in chemistry and biology. A solid-state analogy of solvation is polaron formation, but the magnitude of Coulomb screening is typically an order-of-magnitude weaker than that of solvation in aqueous solutions. Here the PI aims to explore a new class of polarons, the ferroelectric large polaron, which allows efficient Coulomb screening of an electron or hole by extended ordering of dipoles from symmetry-broken unit cells. This kind of local ordering is reflected in the ferroelectric-like THz dielectric responses of lead halide perovskites (LHPs) and may be partially responsible for their exceptional optoelectronic performances. A charge carrier may be localized to and/or induce the formation of nanoscale domain boundaries of locally ordered dipoles in a ferroelectric or paraelectric material, i.e., crystal structure with polar unit cells or polar fluctuations. The ability to form ferroelectric large polarons can result in the efficient screening of charge carriers from scattering with other charge carriers, with charged defects, and with longitudinal optical phonons, thus contributing to enhanced optoelectronic properties. During the past funding period, the PI has explored efficient charge carrier screening in three-dimensional (3D) LHP crystals and has developed the ferroelectric large polaron model to explain a range of carrier properties in these materials. The PI has also developed a new experimental tool, two-dimensional optical Kerr effect (2D-OKE), which is particularly powerful in probing photophysical properties with exquisite energy resolution at or near the bandgap. During the next funding periods, the PI aims to establish the applicability of the ferroelectric large polaron proposal as a general principle for the design/search of defect tolerant semiconductors in optoelectronics. Preliminary experiments on model semiconductor systems beyond LHPs have demonstrated the feasibility of the proposed research.

36 MATERIALS SCIENCE↗

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗

Cost details from front-end engineering design of piperazine with the advanced stripper

This Front-End Engineering Design (FEED) was funded by the U.S. Department of Energy (DOE) to estimate the cost to capture and compress 90% of the CO 2 from an existing natural gas combined cycle (NGCC) in Denver City, Texas, USA. The FEED used the PZAS (Piperazine with the Advanced Stripper) 2G amine scrubbing technology developed and modeled by The University of Texas at Austin. This FEED is unique in providing more public cost details than other FEEDs funded by DOE. The primary objective of the FEED was to provide a comprehensive estimate for the total installed cost of the capture plant. The estimated capital cost of NGCC at the Mustang Station is $\$727$ million for a capacity of 460 MW and 1.6 million tonnes CO 2 /yr. This includes a contingency of $\$104.6$ million and a contractor’s profit of $\$60.1$ million. The total direct field cost is $\$384.1$ million. With an optimistic fuel value of $\$3$/MMBtu, the estimated cost of capture varies from $\$85$/t at 4% IRR/85% load to $\$170$/t at 10% IRR/52% load. Air cooling is technically feasible but expensive. The air cooling systems for the water wash and pump-around intercooling account for 23.4% of the direct cost. The gas-fired boilers represent only 4% of the direct costs, but steam extraction would reduce energy cost, free up cooling water, and reduce the direct costs of processing additional flue gas and CO 2 from the boilers. The absorbers represent 9.6% of the direct cost in this FEED with no direct contact cooler and only 7.6 m of packing. Furthermore, the solvent cross exchangers are less expensive than expected (2.5% of direct costs). Doubling the number of these exchangers could reduce the heat duty from 3.0 to 2.5 GJ/t CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗