SEARCH · Engineering Papers

Results for “gap analysis”

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.

SourceResearch connectionFrom yearThrough year

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

At least 847 records · Page 47

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Superconducting properties and gap structure of the topological superconductor candidate Ti 3 Sb

Here, we present a study of the superconducting properties of the candidate topological superconductor Ti 3 Sb. Electrical transport measurements show zero resistance with a T c,onset of ≈ 5.9 K with a transition width ΔT c ≈ 0.6 K. The superconducting phase boundaries as derived from magnetotransport and magnetic susceptibility measurements agree well. We estimate an upper critical field B c2 (0) ≈ 4.5 T. A Ginzburg-Landau (GL) analysis yields values of the coherence length and penetration depth of ξ = 6.2 nm and λ = 340 nm, respectively, and a GL parameter κ ≈ 55, indicating extreme type-II behavior. Furthermore, we observe a step height in the specific heat $\frac{Δ C_e}{γ T_c}$ ≈ 1.61 ± 0.24 (with T c = 4.8 ± 0.4 K), a value larger than the Bardeen-Cooper-Schrieffer value of 1.43, suggesting modest coupling. Measurements of the temperature dependence of the London penetration depth via the tunnel-diode oscillator technique down to ≈ 450 mK show a full superconducting gap, consistent with a conventional s-wave gap structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

MOA-2009-BLG-319Lb: A Sub-Saturn Planet inside the Predicted Mass Desert

We present an adaptive optics (AO) analysis of images from the Keck II telescope NIRC2 instrument of the planetary microlensing event MOA-2009-BLG-319. The ∼10 yr baseline between the event and the Keck observations allows the planetary host star to be detected at a separation of 66.5 ± 1.7 mas from the source star, consistent with the light-curve model prediction. The combination of the host star brightness and light-curve parameters yields host star and planet masses of M {sub host} = 0.524 ± 0.048M {sub ⊙} and m {sub p} = 67.3 ± 6.2M {sub ⊕} at a distance of D {sub L} = 7.1 ± 0.7 kpc. The star−planet projected separation is 2.03 ± 0.21 au. The planet-to-star mass ratio of this system, q = (3.857 ± 0.029) × 10{sup −4}, places it in the predicted “planet desert” at 10{sup −4} < q < 4 × 10{sup −4} according to the runaway gas accretion scenario of the core accretion theory. Seven of the 30 planets in the Suzuki et al. sample fall in this mass ratio range, and this is the third with a measured host mass. All three of these host stars have masses of 0.5 ≤ M {sub host}/M {sub ⊙} ≤ 0.7, which implies that this predicted mass ratio gap is filled with planets that have host stars within a factor of two of 1M {sub ⊙}. This suggests that runaway gas accretion does not play a major role in determining giant planet masses for stars somewhat less massive than the Sun. Our analysis has been accomplished with a modified DAOPHOT code that has been designed to measure the brightness and positions of closely blended stars. This will aid in the development of the primary method that the Nancy Grace Roman Space Telescope mission will use to determine the masses of microlens planets and their hosts.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Low-phase-noise surface-acoustic-wave oscillator using an edge mode of a phononic band gap

Low-phase-noise microwave-frequency integrated oscillators provide compact solutions for various applications in signal processing, communications, and sensing. Surface acoustic waves (SAWs), featuring orders-of-magnitude shorter wavelength than electromagnetic waves at the same frequency, enable integrated microwave-frequency systems with much smaller footprint on chip. SAW devices also allow higher-quality (Q) factors than electronic components at room temperature. Here, we demonstrate a low-phase-noise gigahertz-frequency SAW oscillator on 128°Y-cut lithium niobate, where the SAW resonator occupies a footprint of 0.05 mm 2 . Leveraging phononic crystal band-gap-edge modes to balance between Q factors and insertion losses, our 1-GHz SAW oscillator features a low phase noise of -132.5 dBc/Hz at a 10-kHz offset frequency and an overlapping Hadamard deviation of 6.5 × 10 -10 at an analysis time of 64 ms. The SAW resonator-based oscillator holds high potential in developing low-noise sensors and acousto-optic integrated circuits.

42 ENGINEERING↗

DOE OSTI2022

Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley's K-function

This work presents novel multiscale spatial data analytics using Ripley's K-function, as a measure of spatial interaction, to study one-dimensional arrangement of fractures. Fracture spatial arrangements are classified into clustered, anticlustered, or indistinguishable from random by testing statistical significance of the calculated Ripley's K-function. Characterizations of fracture arrangements are performed as a function of length scale and position. Analysis of the K-function along the study interval identifies where fracture clustering and anticlustering occur. Here, a simulation technique is also introduced here to statistically reconstruct spatial arrangements and to generate fracture realizations that are spatially similar to the fractures observed in the field. With this simulation technique, one can also fill spatial gaps in fracture measurements where data are absent, unreliable, or unused. Synthetic as well as field-measured 1D fracture datasets are used for testing and demonstration. Methods introduced in this work can be readily applied to fracture datasets observed in outcrops, borehole image logs, and cores.

58 GEOSCIENCES↗

DOE OSTI2021

Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States

This study evaluated the economic feasibility of fast pyrolysis biorefineries fed with blended pine residues and switchgrass in the Southeastern U.S. with different supply chain design. Previous techno-economic analyses (TEA) have focused on either blended biomass or decentralized preprocessing without investigating the impacts of varied process parameters, technology options, and real-world biomass distribution. This study fills the literature gap by modeling scenarios for different biomass blending ratios, biorefinery and preprocessing site (so-called depot) capacities, and alternative preprocessing technologies. High-resolution, real-world geospatial data were analyzed using Geographic Information Systems to facilitate supply chain design and TEA. For a decentralized system, the minimum fuel selling price (MFSP) of biofuel was 3.92–4.33 per gallon gasoline equivalent (GGE), while the MFSP for the centralized biorefinery at the same capacities ranged between 3.75–4.02/GGE. Implementing a high moisture pelleting process depot rather than a conventional pelleting process lowered the MFSP by 0.03–0.17/GGE. Scenario analysis indicated decreased MFSP with increasing biorefinery capacities but not necessarily with increasing depot size. Medium-size depots (500 OMDT/day) achieved the lowest MFSP. Here, this analysis identified the optimal blending ratios for two preprocessing technologies at varied depot sizes. Counterintuitively, increasing the proportion of higher cost switchgrass reduced the MFSP for large biorefineries (>5000 ODMT/day), but increased the MFSP for small biorefineries (1000–2500 ODMT/day). Although the decentralized systems have a higher MFSP based on current analysis, it has other potential benefits such as mitigated supply chain risks and improved feedstock quality that are difficult to be quantified in this TEA.

09 BIOMASS FUELS↗

DOE OSTI2024

Introducing NOODLES: Collaborative Visualization in a Flavorful Package

We introduce NOODLES, a lightweight collaborative visualization and analysis protocol. NOODLES was developed to enable new scientific workflows while enhancing existing pipelines. Using a technology-minimal approach to strengthen applicability, this protocol allows researchers to tie disparate software together as well as making domain specific visualizations accessible across various platforms and form factors. In this talk we discuss background, challenges, and gaps in the current tool landscape that lead to the development of the protocol. We then describe the design of the protocol and present several use cases to demonstrate the efficacy of NOODLES in addressing complex visualization challenges and how it co-exists with existing tools. We conclude by outlining in-progress work and potential avenues for future development within the NOODLES framework.

collaborative analysis↗

DOE OSTI2026

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Assessment of the driving factors of CO 2 mitigation costs of household biogas systems in China: A LMDI decomposition with cost analysis model

China has been placing a substantial focus on biogas for reducing energy consumption and carbon dioxide (CO 2 ) emissions. The operation mode of biogas systems may make the CO 2 reduction target over-optimistic. There is limited research to investigate the influential factors that may be causing the gap between the actual and theoretical CO 2 reduction costs of biogas systems in China. In this research, by using field survey data of 209 biogas users and 489 non-biogas users from 19 villages in 2015, the gap between actual and theoretical unit CO 2 reduction cost is quantified at approximately 156 USD/t CO 2 . By employing the Logarithmic Mean Divisia Index I (LMDI) model, it is found that both the cost effect (48%) and the reduction effect (52%) contribute to the unit CO 2 reduction cost gap. Furthermore, four influential factors–household labor, accessibility to the energy resource, acceptance of biogas technology, and subsidy–significantly narrow the gap between actual and theoretical CO 2 reduction costs, while the levelized subsidy contributes to widening the gap. On average, biogas systems should be operated for at least four years and the substitution rate should be more than 67% in order to keep the gap between actual and theoretical CO 2 reduction costs under 50%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Nonadiabatic dynamics of photoexcited thiopyridone isomers: An interplay between El-Sayed’s conditions and energy gap law

We investigated the non-adiabatic dynamics of photoexcited thiopyridone systems across their ortho-, meta-, and para-isomeric forms. The relaxation pathways of the three isomers in both gas phase and solvent environments are mapped using surface hopping dynamics based on time-dependent density functional theory. Our analysis highlights the influence of isomeric structures on photophysical behavior, offering insights into design principles to control photochemical phenomena. The simulations suggest a systematic reduction in the rate of intersystem crossing (ISC) from ortho- to meta- to para-isomer. Comparisons with multiconfigurational wave function methods in the gas phase further demonstrate how electronic structure influences the predicted dynamical pathways. The simulated dynamics demonstrates that the spin–orbit coupling strength alone does not determine the rate of ISC, as both state energetics and underlying electronic and structural features play decisive roles. These aspects explain the much slower ISC in the para-isomer, as well as the non-negligible role of the El-Sayed forbidden pathway in the computed ISC dynamics.

Complete-active space self-consistent field↗

DOE OSTI2024

Measurement bias in self-heating x-ray free electron laser experiments from diffraction studies of phase transformation in titanium

X-ray self-heating is a common by-product of X-ray Free Electron Laser (XFEL) techniques that can affect targets, optics, and other irradiated materials. Diagnosis of heating and induced changes in samples may be performed using the x-ray beam itself as a probe. However, the relationship between conditions created by and inferred from x-ray irradiation is unclear and may be highly dependent on the material system under consideration. Here, we report on a simple case study of a titanium foil irradiated, heated, and probed by a MHz XFEL pulse train at 18.1 keV delivered by the European XFEL using measured x-ray diffraction to determine temperature and finite element analysis to interpret the experimental data. We find a complex relationship between apparent temperatures and sample temperature distributions that must be accounted for to adequately interpret the data, including beam averaging effects, multivalued temperatures due to sample phase transitions, and jumps and gaps in the observable temperature near phase transformations. The results have implications for studies employing x-ray probing of systems with large temperature gradients, particularly where these gradients are produced by the beam itself. Finally, this study shows the potential complexity of studying nonlinear sample behavior, such as phase transformations, where biasing effects of temperature gradients can become paramount, precluding clear observation of true transformation conditions.

Crystallography↗

DOE OSTI2020

Observation of gapped state in rare-earth monopnictide HoSb

The rare-earth monopnictide family is attracting an intense current interest driven by its unusual extreme magnetoresistance (XMR) property and the potential presence of topologically non-trivial surface states. The experimental observation of non-trivial surface states in this family of materials are not ubiquitous. Here, using high-resolution angle-resolved photoemission spectroscopy, magnetotransport, and parallel first-principles modeling, we examine the nature of electronic states in HoSb. Although we find the presence of bulk band gaps at the G and X-symmetry points of the Brillouin zone, we do not find these gaps to exhibit band inversion so that HoSb does not host a Dirac semimetal state. Our magnetotransport measurements indicate that HoSb can be characterized as a correlated nearly-complete electron-hole-compensated semimetal. Our analysis reveals that the nearly perfect electron-hole compensation could drive the appearance of non-saturating XMR effect in HoSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

First-principles theory of direct-gap optical emission in hexagonal Ge and its enhancement via strain engineering

The emergence of hexagonal Ge (2H-Ge) as a candidate direct-gap group-IV semiconductor for Si photonics mandates a rigorous understanding of its optoelectronic properties. Theoretical predictions of a “pseudodirect” band gap, characterized by weak oscillator strength, contrast with a claimed high radiative recombination coefficient 𝐵 comparable to conventional (cubic) InAs. We compute 𝐵 in 2H-Ge from first principles and quantify its dependence on temperature, carrier density, and strain. For unstrained 2H-Ge, our calculated spontaneous emission spectra corroborate that measured photoluminescence corresponds to direct-gap emission, but with 𝐵 being approximately three orders of magnitude lower than in InAs. We confirm a pseudodirect-to-direct-gap transition under ∼2% [0001] uniaxial tension, which can enhance 𝐵 by up to 3 orders of magnitude, making it comparable to that of InAs. Beyond quantifying the strong enhancement of 𝐵 via strain engineering, our analysis suggests the dominance of additional, as-yet unquantified recombination mechanisms in this nascent material.

36 MATERIALS SCIENCE↗

DOE OSTI2022

University of Missouri Research Reactor (MURR) LEU Fuel Fluid-Structure Interaction Analysis

The University of Missouri Research Reactor (MURR ® ) is one of five U.S. high performance research reactors (USHPRR), plus one critical facility, that are actively collaborating with the National Nuclear Security Administration (NNSA) Material Management and Minimization (M 3 ) Reactor Conversion Program to convert from highly enriched uranium (HEU, ≥ 20 wt.% U-235) to low-enriched uranium (LEU, < 20 wt.% U-235) fuel. A new type of LEU fuel with very high density, based on an alloy of uranium and 10 weight percent molybdenum (U-10Mo), is expected to allow the conversion to LEU of USHPRR that have been found unable to be converted with previously qualified uranium silicide-aluminum (U 3 Si 2 -Al) dispersion fuel. MURR has been working with the USHPRR Reactor Conversion (RC) Pillar at Argonne National Laboratory to perform fuel element design and fuel cycle performance analyses, steady-state thermal hydraulics safety analyses, and accident safety analyses in preparation for the conversion of MURR and to support a preliminary Safety Analysis Report (SAR) for conversion to LEU fuel. In this work, Fluid-structure interaction (FSI) analysis at the fuel element level, as compared to the fuel plate level of the previous work. is performed which models all components of the MURR LEU fuel element, including fuel plates and the supporting structures e.g., side plates, end fittings, and combs. Therefore, the effect of supporting structures on the coolant flow distribution, the fuel plate deflection, and the resulting coolant channel gap reduction can be evaluated. In addition to the nominal element geometry and flow rate, the tolerances in the geometry dimensions of coolant channel and plate thickness, the effect of a comb on plate deflection, and the uncertainty of the flow rate per element are considered in this work. The effect of comb on plate displacement is quantified through two bounding cases: the case assuming a perfect bond between the comb and plates and the case neglecting the comb effect. Note that in this analysis, the FSI has been decoupled from the other structural effects caused by irradiation (e.g., swelling and irradiation creep). Assessment of combined effects is planned for a later stage of this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗

DOE OSTI2024

Securing Solar for the Grid: Spring 2024 IAB Meeting

The Spring 2024 IAB meeting will focus on updates from the research team and collective feedback and inputs for an updated Roadmap for Solar Cybersecurity. Researchers from the four DOE National Laboratories will present with industry counterparts for the major research tasks within the S2G program, including: Solar Cybersecurity Standards and Certifications, Solar Risk Assessments & Mitigation, Solar Supply Chain Assessment, Network Monitoring Tools and Analysis, and Training and Workforce Development. Sandia National Laboratories developed an original Roadmap for PV Cybersecurity in 2017. This year, we are updating that roadmap to reflect the current state of research and industry and identify gaps and priorities still to be addressed. We look forward to the IAB’s input on key topics for the roadmap.

14 SOLAR ENERGY↗

DOE OSTI2024

Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

09 BIOMASS FUELS↗

DOE OSTI2024

Supporting data for Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Li, Shuyun↗