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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Continuous multimodal technologies in industrial microbiology: potential for achieving high process performance and agility

The field of industrial microbiology has great potential to tackle the most pressing challenges facing society, but today, this entails much more than classical fermentation technology followed by product upgrading. Methods are needed to confer unit-operation-level functionality and whole-system-level robustness, as well as flexibility. As examples of this concept, we focus here on methodologies often deployed at industrial scale as discrete processes—such as biological, chemical, and electrochemical unit operations—that are also capable of substantial complementarity when combined sequentially and operated continuously. A key and relatively new type of conversion step is made possible by catalyst immobilization methods at both the enzymatic and cellular level. Cases drawn from electro-fermentation for acetoin production and syngas-mediated microbial electrosynthesis of ethanol exemplify the synergy of combined operational approaches. Because modular processes can be treated as a series of reactor elements, considerable flexibility is possible. As discussed, however, not all processes are amenable to this intensification.

09 BIOMASS FUELS↗
DOE OSTI2023

A Multi-Dimensional Benefit Assessment of Automated Mobility Platforms (AMP) for Large Facilities: Mobility, Energy, Equity, and Facility Management & Design

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability - both of which are important metrics often overlooked during the engineering design process. Therefore, to evaluate systems and inform critical near- and long-term decisions more effectively, a holistic evaluation framework is proposed focused on four key areas: (1) mobility, with emphasis on travel time and accessibility within an airport, (2) environment, focused on energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, (3) equity, specifically to the PRM community, but with an eye to the whole of society, and (4) built environment, or the fundamental changes in building design enabled by different mobility systems for larger and more flexible, functional, and energy-efficient structures. Below, AMPs are defined, and each metric is discussed further, all with a focus on airport mobility.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Algae Biofilm Produced from Anaerobic Digester Wastewater Demonstrated as Biofertilizer for Dwarf Wheat

Aims: To correlate yield of dwarf wheat fertilized with algae biofilm produced using anaerobic digester effluent (digestate) from a municipal water resource recovery facility as nutrient source and compare with yield using non-algae biofilm based fertilizers and a negative control. Study Design: Greenhouse testing for measurement of biomass yields and statistical analysis of wheat yield data results. Place and Duration of Study: Department of Biological Engineering Algae Processing and Products Facility greenhouse between March and June, 2024. Methodology: Yield of a dwarf cultivar of red spring wheat was measured as a function of four treatments including three fertilizers and a negative control: (1) algae biofilm cultivated on anaerobic digester effluent, (2) positive control of Osmocote commercial slow release fertilizer, (3) anaerobic digester biosolids, and (4) negative control with no fertilizer addition. Results: Average yield values (gm) for the four treatments were: (1) 1.25, (2) 0.99, (3) 0.72, and (4) 0.52, respectively. Algae biofilm fertilizer performed significantly better than Osmocote with P = .002, anaerobic digester biosolids with P = .05, and no fertilizer addition with P = .05. Struvite, a slow release fertilizer, was observed to be associated with the algae biofilm as a precipitate of the high concentrations of nutrients within the anaerobic digester water. Struvite (MgNH4PO46H2O) releases plant available nitrogen and phosphorus over time and is biologically precipitated due to the increase in solution pH as a result of photosynthesis by the algae biofilm. Conclusion: Algae biofilm cultivated on anaerobic digester wastewater can serve as a biofertilizer for recycling nutrients within the biosphere for sustainable nutrient management.

09 BIOMASS FUELS↗
DOE OSTI2021

Machine Learning Tools Set for Natural Gas Fuel Cell System Design

This study is focusing on leveraging the system design tools set for the next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system. Conventionally, system design and optimization of NGFC systems rely heavily on traditional reduced order model (ROM) techniques and designers’ experience level. For overcoming the technical barriers of system design, multiple multi-physics models and machine learning (ML) tools have been utilized to automate the conceptual design process and enhance the reliability of solutions for the NGFC system. The proposed tools set includes a physics-informed ML tool for automated ROM construction that leverages advances in deep neural networks to significantly reduce ROM prediction error for the NGFC power island compared to traditional approaches. The constructed physics-informed ML ROM can be used in system design, and optimization tools set Institute for the Design of Advanced Energy Systems (IDAES) Process Systems Engineering (PSE) framework. The tools set also provides a user-friendly graphic user interface built within Jupyter Notebooks, and the complete tools set is open-source public available.

Wang, Dewei↗
DOE OSTI2020

Biodiesel production from engineered sugarcane lipids under uncertain feedstock compositions: Process design and techno-economic analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($\$96.5$ million) and minimum MSP ($\$1107$ /ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($\$0.536$ /kg) results in a positive NPV. When the cane lipid price is higher (> $\$0.80$ /kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, Here, the best-case scenario revealed that the minimum NPV under any process scheme could yield more than $\$100$ million (or MSP: $\$0.80$ /L), and the worst-case analysis showed that losses incurred by the plant could be as high as 80 million (MSP: $\$1.36$ /L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

09 BIOMASS FUELS↗
DOE OSTI2020

Data from Biodiesel Production from Engineered Sugarcane Lipids under Uncertain Feedstock Compositions: Process Design and Techno-Economic Analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($96.5 million) and minimum MSP ($1107/ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($0.536/kg) results in a positive NPV. When the cane lipid price is higher (>$0.80/kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, The best-case scenario revealed that the minimum NPV under any process scheme could yield more than $100 million (or MSP: $0.80/L), and the worst-case analysis showed that losses incurred by the plant could be as high as $80 million (MSP: $1.36/L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

Conversion↗
DOE OSTI2021

Editorial: Multi-Omics Technologies for Optimizing Synthetic Biomanufacturing

Industrial manufacturing endures as an essential human activity yielding a variety of useful products; it plays a significant role in the global economy with huge impacts in everyday life. However, the manufacturing process requires consumption of various raw materials (especially petroleum derivatives), generates a variety of harmful waste products, causes pollution, and is energetically inefficient. Biological manufacturing from sustainable, affordable, and scalable feedstocks potentially enables the displacement of the entire portfolio of currently available products produced by industrial processes, enabling the manufacturing of renewable and eco-friendly products (Clomburg et al., 2017). Thus, successful development of a robust biomanufacturing strategy and technology platform, based on the latest advances in synthetic biology and chemical catalysis, will decrease both the cost and production time compared with previous manufacturing processes. Development of biomanufacturing processes using a synthetic biology platform requires the multidisciplinary efforts of science and engineering fields including molecular biology, microbiology, genetic engineering, informatics, metabolic modeling and chemical or process engineering (El Karoui et al., 2019).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Novel Hot Gas Components for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

Additive Manufacturing (AM), also known as 3D printing, has emerged as a manufacturing method that enables new design freedom for gas turbine engine manufacturers. However, the material selection for AM processable high-temperature super alloys is currently limited. Additionally, the heat transfer performance of AM enabled micro-cooling architectures is not yet well understood. Accordingly, in support of advanced manufacturing and engine performance development, Oak Ridge National Laboratory (ORNL)and Solar Turbines (Solar) conducted a multidisciplinary project to generate both AM super alloy material properties data and micro-channel performance data for two AM super alloys. The data supported the design and analysis of an internally cooled turbine hot section AM tip shoe component. This data was used to analytically predict the reduction in operating temperature of a gas turbine tip shoe. The work concluded that the cooling flow required to cool the tip shoe can be tuned to suit the efficiency improvements desired in an industrial gas turbine.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report

The Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report outlines key insights and actionable recommendations for accelerating the scale-up of disruptive chemical manufacturing technologies. Convened in October 2024, the workshop brought together approximately fifty experts from academia, industry, national laboratories, and government agencies to address the barriers and solutions for maturing technologies from proof-of-concept to commercialization. The report identifies seven critical themes for enabling faster scale-up. These themes were explored through general discussions and breakout sessions focused on three specific chemical manufacturing technologies—electrochemical, thermochemical, and biological conversion processes. The findings emphasize the importance of interdisciplinary collaboration, robust funding mechanisms, and shared resources to overcome technical barriers and accelerate technology deployment. The report also highlights technology-specific challenges and opportunities, including the need for advanced materials, scalable manufacturing processes, and integrated testing environments. For electrochemical manufacturing processes, durability and material optimization are key priorities, while thermochemical processes require novel reactor designs and better supply chain integration. Biological conversion processes face hurdles in strain engineering, reactor design, and process integration. Across all technologies, the workshop emphasized the importance of leveraging computational tools, standardized protocols, and collaborative networks to address knowledge gaps and technical barriers. By acting on these insights, stakeholders can reduce the timeline for scaling up critical chemical manufacturing technologies, ensuring their timely impact on manufacturing competitiveness, and environmental sustainability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Integrated system failure analysis software toolchain (IS-FAST)

Systems and methods are provided for generating faults and analyzing fault propagation and its effects. Starting from the ontologies of components, functions, flows, and faults, systems and methods are provided that describe, generate and track faults in a computer system across multiple domains throughout design and/or development. In order to construct the system and fault models, a series of concepts is introduced in the form of ontologies and their dependencies. An investigation is performed into the faults, including their type, cause, life-cycle aspects, and effect. Principles and rules are created to generate various faults based on system configurations. After the modeling process, a simulation engine is described to execute actions and simulate the process of fault generation and propagation. As a result, fault paths that impact components and functions can be obtained.

Diao, Xiaoxu↗
DOE OSTI2022

Investigation of near-field jet stability of a single-hole injector based on fast X-ray phase contrast imaging and image feature matching

Fuel spray is very effective in controlling the combustion process to improve engine performance and reduce emissions. Understanding the spray unstability during the injection process is of importance to improve the control of spray characteristics and engine operation. In this study, near-field biodiesel jets were recorded using fast X-ray phase contrast imaging and the flow features inside the jet were extracted using Speeded Up Robust Features (SURF) method. Here, the image similarity by feature matching was successfully used to represent the near-field jet stability. Based on the jet stability, an injection process can be divided into five stages: an unstable stage at needle opening, a partially stable transition stage at needle opening, a stable stage, a stable transition stage at needle closing and an unstable stage at needle closing. The ranges of needle lift for five stages were also determined. The jet unstability is highly related to the cavitation formation and gas purging process during needle opening. The variation of stable jet feature is dependent on the needle lift at needle closing. Higher needle lift for the similar jet feature at needle opening indicates a hydraulic delay compared to needle closing. Finally, the possible reasons of jet feature formation and feature detection used on the multi-hole injector are discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. In conclusion, quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Tidal Turbine Benchmarking Project: Stage I - Steady Flow Blind Predictions: Preprint

This paper presents the first blind prediction stage of the Tidal Turbine Benchmarking Project being conducted and funded by the UK's EPSRC and Supergen ORE Hub. In this first stage, only steady flow conditions, at low and elevated turbulence (3.1%) levels, were considered. Prior to the blind prediction stage, a large laboratory scale experiment was conducted in which a highly instrumented 1.6m diameter tidal rotor was towed through a large towing tank in well-defined flow conditions with and without an upstream turbulence grid. Details of the test campaign and rotor design were released as part of this community blind prediction exercise. Participants were invited to use a range of engineering modelling approaches to simulate the performance and loads of the turbine. 26 submissions were received from 12 groups from across academia and industry using solution techniques ranging from blade resolved computational fluid dynamics through actuator line, boundary integral element methods, vortex methods to engineering Blade Element Momentum methods. The comparisons between experiments and blind predictions were extremely positive helping to provide validation and uncertainty estimates for the models, but also validating the experimental tests themselves. The exercise demonstrated that the experimental turbine data provides a robust data set against which researchers and design engineers can test their models and implementations to ensure robustness in their processes, helping to reduce uncertainty and provide increased confidence in engineering processes. Furthermore, the data set provides the basis by which modellers can evaluate and refine approaches.

benchmarking↗
DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Framework for a Digital Documented Safety Analysis

This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Overcoming barriers to medium-chain fatty alcohol production

Medium-chain fatty alcohols ( mc FaOHs) are aliphatic primary alcohols containing six to twelve carbons that are widely used in materials, pharmaceuticals, and cosmetics. Microbial biosynthesis has been touted as a route to less-abundant chain-length molecules and as a sustainable alternative to current petrochemical processes. Several metabolic engineering strategies for producing mc FaOHs have been demonstrated in the literature, yet processes continue to suffer from poor selectivity and mc FaOH toxicity, leading to reduced titers, rates, and yields of the desired compounds. Here, this opinion examines the current state of microbial mc FaOH biosynthesis, summarizing engineering efforts to tailor selectivity and improve product tolerance by implementing engineering strategies that circumvent or overcome mc FaOH toxicity.

59 BASIC BIOLOGICAL SCIENCES↗