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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Data for Engineering and Evolution of Yarrowia lipolytica for Producing Lipids from Lignocellulosic Hydrolysates

Yarrowia lipolytica , an oleaginous yeast, shows promise for industrial fermentation due to its robust acetyl-CoA flux and well-developed genetic engineering tools. However, its lack of an active xylose metabolism restricts the conversion of cellulosic sugars to valuable products. To address this, metabolic engineering, and adaptive laboratory evolution (ALE) were applied to the Y. lipolytica PO1f strain, resulting in an efficient xylose-assimilating strain (XEV). Whole-genome sequencing (WGS) of the XEV followed by reverse engineering revealed that the amplification of the heterologous oxidoreductase pathway and a mutation in the GTPase-activating protein gene (YALI0B12100g) might be the primary reasons for improved xylose assimilation in the XEV strain. When a sorghum hydrolysate was used, the XEV strain showed superior xylose consumption and lipid production compared to its parental strain (X123). This study advances our understanding of xylose metabolism in Y. lipolytica and proposes effective metabolic engineering strategies for optimizing lignocellulosic hydrolysates.

Hydrolysate↗
DOE OSTI2025

Cyber-Informed Engineering (CIE) Integration into Model- Based Systems Engineering (MBSE)

Engineering design in the field of industrial engineering, such as designing automated factories or warehouses, is critical for the effective operation of facilities. Any design flaws introduced early can result in significant capital expenses to correct. However, early-stage engineering design is inherently complex. The systems are not yet built, requiring designers to integrate various aspects, including digital engineering and cybersecurity, to support virtual representations throughout the design process. In this study, we propose an approach to integrate Cyber-Informed Engineering (CIE) principles into model-based systems engineering (MBSE). This approach facilitates the development of a digital thread for engineering systems, ensuring secure digital artifacts in the design of industrial engineering systems.

42 - ENGINEERING↗
NASA NTRS1949

Analysis of Performance of Jet Engine from Characteristics of Components II : Interaction of Components as Determined from Engine Operation

In order to understand the operation and the interaction of jet-engine components during engine operation and to determine how component characteristics may be used to compute engine performance, a method to analyze and to estimate performance of such engines was devised and applied to the study of the characteristics of a research turbojet engine built for this investigation. An attempt was made to correlate turbine performance obtained from engine experiments with that obtained by the simpler procedure of separately calibrating the turbine with cold air as a driving fluid in order to investigate the applicability of component calibration. The system of analysis was also applied to prediction of the engine and component performance with assumed modifications of the burner and bearing characteristics, to prediction of component and engine operation during engine acceleration, and to estimates of the performance of the engine and the components when the exhaust gas was used to drive a power turbine.

Goldstein, Arthur W↗
NASA NTRS2001

Space Shuttle Main Engine Joint Data List Applying Today's Desktop Technologies to Facilitate Engine Processing

Boeing-Rocketdyne's Space Shuttle Main Engine (SSME) is the world's first large reusable liquid rocket engine. The space shuttle propulsion system has three SSMEs, each weighing 7,400 lbs and providing 470,000 lbs of thrust at 100% rated power level. To ensure required safety and reliability levels are achieved with the reusable engines, each SSME is partially disassembled, inspected, reassembled, and retested at Kennedy Space Center between each flight. Maintenance processing must be performed very carefully to replace any suspect components, maintain proper engine configuration, and avoid introduction of contaminants that could affect performance and safety. The long service life, and number, complexity, and pedigree of SSME components makes logistics functions extremely critical. One SSME logistics challenge is documenting the assembly and disassembly of the complex joint configurations. This data (joint nomenclature, seal and fastener identification and orientation, assembly sequence, fastener torques, etc.) must be available to technicians and engineers during processing. Various assembly drawings and procedures contain this information, but in this format the required (practical) joint data can be hard to find, due to the continued use of archaic engineering drawings and microfilm for field site use. Additionally, the release system must traverse 2,500 miles between design center and field site, across three time zones, which adds communication challenges and time lags for critical engine configuration data. To aid in information accessibility, a Joint Data List (JDL) was developed that allows efficient access to practical joint data. The published JDL has been a very useful logistics product, providing illustrations and information on the latest SSME configuration. The JDL identifies over 3,350 unique parts across seven fluid systems, over 300 joints, times two distinct engine configurations. The JDL system was recently converted to a web-based, navigable electronic manual that contains all the required data and illustrations in expanded view format using standard PC products (Word, Excel, PDF, Photoshop). The logistics of accurately releasing this information to field personnel was greatly enhanced via the utilization of common office products to produce a more user-friendly format than was originally developed under contract to NASA. This was done without reinventing the system, which would be cost prohibitive on a program of this maturity. The brunt of the joint part tracking is done within the logistics organization and disseminated to all field sites, without duplicating effort at each site. The JDL is easily accessible across the country via the NASA intranet directly at the SSME workstand. The advent of this logistics data product has greatly enhanced the reliability of tracking dynamic changes to the SSME and greatly reduces engineering change turnaround time and potential for errors. Since the inception of the JDL system in 1997, no discrepant parts have propagated to engine assembly operations. This presentation focuses on the challenges overcome and the techniques used to apply today's desktop technologies to an existing logistics data source.

Jacobs, Kenneth↗
NASA NTRS2004

Exo-Skeletal Engine: Novel Engine Concept

The exo-skeletal engine concept represents a new radical engine technology with the potential to substantially revolutionize engine design. It is an all-composite drum-rotor engine in which conventionally heavy shafts and discs are eliminated and are replaced by rotating casings that support the blades in spanwise compression. Thus the rotating blades are in compression rather than tension. The resulting open channel at the engine centerline has immense potential for jet noise reduction and can also accommodate an inner combined-cycle thruster such as a ramjet. The exo-skeletal engine is described in some detail with respect to geometry, components, and potential benefits. Initial evaluations and results for drum rotors, bearings, and weights are summarized. Component configuration, assembly plan, and potential fabrication processes are also identified. A finite element model of the assembled engine and its major components is described. Preliminary results obtained thus far show at least a 30-percent reduction of engine weight and about a 10-dB noise reduction, compared with a baseline conventional high-bypass-ratio engine. Potential benefits in all aspects of this engine technology are identified and tabulated. Quantitative assessments of potential benefits are in progress.

Chamis, Cristos C.↗
NASA NTRS2005

Engineering Lessons Learned and Systems Engineering Applications

Systems Engineering is fundamental to good engineering, which in turn depends on the integration and application of engineering lessons learned and technical standards. Thus, good Systems Engineering also depends on systems engineering lessons learned from within the aerospace industry being documented and applied. About ten percent of the engineering lessons learned documented in the NASA Lessons Learned Information System are directly related to Systems Engineering. A key issue associated with lessons learned datasets is the communication and incorporation of this information into engineering processes. Systems Engineering has been defined (EINIS-632) as "an interdisciplinary approach encompassing the entire technical effort to evolve and verify an integrated and life-cycle balanced set of system people, product, and process solutions that satisfy customer needs". Designing reliable space-based systems has always been a goal for NASA, and many painful lessons have been learned along the way. One of the continuing functions of a system engineer is to compile development and operations "lessons learned" documents and ensure their integration into future systems development activities. They can produce insights and information for risk identification identification and characterization. on a new project. Lessons learned files from previous projects are especially valuable in risk

Gill, Paul S.↗
NASA NTRS1947

Altitude Cooling Investigation of the R-2800-21 Engine in the P-47G Airplane. IV - Engine Cooling-Air Pressure Distribution

A study of the data obtained in a flight investigation of an R-2800-21 engine in a P-47G airplane was made to determine the effect of the flight variables on the engine cooling-air pressure distribution. The investigation consisted of level flights at altitudes from 5000 to 35,000 feet for the normal range of engine and airplane operation. The data showed that the average engine front pressures ranged from 0.73 to 0.82 of the impact pressure (velocity head). The average engine rear pressures ranged from 0.50 to 0.55 of the impact pressure for closed cowl flaps and from 0.10 to 0.20 for full-open cowl flaps. In general, the highest front pressures were obtained at the bottom of the engine. The rear pressures for the rear-row cylinders were .lower and the pressure drops correspondingly higher than for the front-row cylinders. The rear-pressure distribution was materially affected by cowl-flap position in that the differences between the rear pressures of the front-row and rear-row cylinders markedly increased as the cowl flaps were opened. For full-open cowl flaps, the pressure drops across the rear-row cylinders were in the order of 0.2 of the impact pressure greater than across the front-row cylinders. Propeller speed and altitude had little effect on the -coolingair pressure distribution, Increase in angle of inclination of the thrust axis decreased the front ?pressures for the cylinders at the top of the engine and increased them for the cylinders at the bottom of the engine. As more auxiliary air was taken from the engine cowling, the front pressures and, to a lesser extent, the rear pressures for the cylinders at the bottom of the engine decreased. No correlation existed between the cooling-air pressure-drop distribution and the cylinder-temperature distribution.

Kaufman, Samuel J.↗
DOE OSTI2025

Enzyme Engineering Database (EnzEngDB): a platform for sharing and interpreting sequence–function relationships across protein engineering campaigns

The discovery and engineering of new enzymes is important across the bioeconomy, with diverse applications from foods to pharmaceuticals, sensors to agriculture. However, enzyme engineering, in particular machine learning-guided engineering, is hampered by a lack of data. Currently there exists no database designed to capture and interpret datasets created in this domain, nor are there easy analysis and visualisation tools. We developed the Enzyme Engineering Database to provide a centralized resource and an online analysis tool to consolidate sequence-function data from enzyme engineering campaigns, thereby making three contributions: (i) a database into which researchers can deposit public data, (ii) visualisation and analysis tools for protein engineers to analyse their own data or compare enzyme variants to other engineering campaigns, and (iii) a gold-standard dataset for benchmarking automated extraction along with the first large language model extraction pipeline specific for enzyme engineering campaigns. The Enzyme Engineering Database is accessible at http://enzengdb.org/.

Long, Yueming [California Institute of Technology ↗
NASA NTRS1977

Booster engines derived from the Space Shuttle Main Engine

Current vehicle studies of post-Space Shuttle vehicles have identified the potential need for a high-pressure booster engine using liquid oxygen/hydrocarbon fuel (RP-1) as propellants. Recent studies of the possibility of using Space Shuttle Main Engine (SSME) components for a high pressure LOX/RP-1 engine have resulted in several engine configurations which are based largely on SSME components. The current SSME thrust chamber is regeneratively cooled with hydrogen using a relatively low percentage of the total hydrogen flow. For a LOX/RP-1 application the SSME thrust chamber can be run at high pressures and be cooled with a relatively low hydrogen flow. In addition, the SSME oxygen pump, valves, and main injector components may be utilized for the booster engine. By using a majority of the current SSME engine components for the LOX/RE-1 booster engine, engine development time and cost can be significantly reduced compared to the development of a new engine.

Sobin, A. J.↗
NASA NTRS1980

Orbit Transfer Vehicle (OTV) advanced expander cycle engine point design study. Task 7: Engine data summary

A performance optimized engine system design for a man-rated advanced LOX/hydrogen expander cycle engine was investigated. The data are presented in tables, figures, and drawings. The following categories of data for the advanced expander cycle engine are presented: engine operating specification and pressure schedule; engine system layout drawing; major component layout drawings, including thrust chamber and nozzle, extendible nozzle actuating mechanism and seal, LOX turbopump, LOX boost pump, hydrogen turbopump, hydrogen boost pump, and propellant control valves; engine performance and service life prediction; engine weight; and engine envelope. The data represent updates based upon current results from the design and analyses tasks performed under contract. Futher iterations in the designs and data can be expected as the advanced expander cycle engine design matures.

Christensen, K. L.↗
NASA NTRS2007

A Return to Innovative Engineering Design, Critical Thinking and Systems Engineering

I believe we are facing a critical time where innovative engineering design is of paramount importance to the success of our aerospace industry. However, the very qualities and attributes necessary for enhancing, educating, and mentoring a creative spirit are in decline in important areas. The importance of creativity and innovation in this country was emphasized by a special edition of the Harvard Business Review OnPoint entitled: "The Creative Company" which compiled a series of past and present articles on the subject of creativity and innovation and stressed its importance to our national economy. There is also a recognition of a lack of engineering, critical thinking and problem-solving skills in our education systems and a trend toward trying to enhance those skills by developing K-12 educational programs such as Project Lead the Way, "Science for All Americans", Benchmarks 2061 , etc. In addition, with respect to spacecraft development, we have a growing need for young to mid-level engineers with appropriate experience and skills in spacecraft design, development, analysis, testing, and systems engineering. As the Director of Engineering at NASA's Johnson Space Center, I realized that sustaining engineering support of an operational human spacecraft such as the Space Shuttle is decidedly different than engineering design and development skills necessary for designing a new spacecraft such as the Crew Exploration Vehicle of the Constellation Program. We learned a very important lesson post Columbia in that the Space Shuttle is truly an experimental and not an operational vehicle and the strict adherence to developed rules and processes and chains of command of an inherently bureaucratic organizational structure will not protect us from a host of known unknowns let alone unknown unknowns. There are no strict rules, processes, or procedures for understanding anomalous results of an experiment, anomalies with an experimental spacecraft like Shuttle, or in the conceptual design of a spacecraft. Engineering design is as much an art as it is a science. The critical thinking skills necessary to uncover lurking problems in an experimental design and creatively develop solutions are some of the same skills necessary to design a new spacecraft. Thus, I believe engineers unfamiliar with or removed from design and development need time to transition and develop the required skill set to be effective spacecraft designers. I believe the creative process necessary in design can be enhanced and even taught as early as grades K-12 and should continue to be nurtured and developed at the university level and beyond. I am going to present a strategy for developing learning teams to address complex multidisciplinary problems and to creatively develop solutions to those problems rapidly at minimal cost. I will frame a real problem, the development of on-orbit thermal protection system repair of the Space Shuttle, and step through the series of skills necessary to enhance the creative process. The case study I will illustrate is based on a real project, the R&D Reinforced Carbon-Carbon (RCC) Repair Team's development of on-orbit repair concepts for damaged Space Shuttle RCC nose cap and/or leading edges.

Camarda, Charles J.↗
DOE OSTI2026

Data for A Generalized Platform for Artificial Intelligence-powered Autonomous Protein Engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-foldimprovement in substrate preference and 16-fold improvement in ethyl-transferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

AI/ML↗
DOE OSTI2025

Cyber-Informed Engineering (CIE) – Engineered Controls Database and Use

Cyber-Informed Engineering (CIE) addresses the reality that cyber-attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This database is meant to establish clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design. The goal is to ensure that resilience is engineered into systems from the outset. Unlike cybersecurity protections that defend the digital layer, engineered controls act directly at the physical and algorithmic levels to guarantee that unacceptable consequences are prevented or limited. CIE keeps the consequences of a cyber attack from impacting the safety, reliability, and performance of engineered systems.

42 - ENGINEERING↗
NASA NTRS2015

Enhanced Engine Performance During Emergency Operation Using a Model-Based Engine Control Architecture

This paper discusses the design and application of model-based engine control (MBEC) for use during emergency operation of the aircraft. The MBEC methodology is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40,000) and features an optimal tuner Kalman Filter (OTKF) to estimate unmeasured engine parameters, which can then be used for control. During an emergency scenario, normally-conservative engine operating limits may be relaxed to increase the performance of the engine and overall survivability of the aircraft; this comes at the cost of additional risk of an engine failure. The MBEC architecture offers the advantage of estimating key engine parameters that are not directly measureable. Estimating the unknown parameters allows for tighter control over these parameters, and on the level of risk the engine will operate at. This will allow the engine to achieve better performance than possible when operating to more conservative limits on a related, measurable parameter.

control theory↗
NASA NTRS2016

Enhanced Engine Performance During Emergency Operation Using a Model-Based Engine Control Architecture

This paper discusses the design and application of model-based engine control (MBEC) for use during emergency operation of the aircraft. The MBEC methodology is applied to the Commercial Modular Aero-Propulsion System Simulation 40k (CMAPSS40k) and features an optimal tuner Kalman Filter (OTKF) to estimate unmeasured engine parameters, which can then be used for control. During an emergency scenario, normally-conservative engine operating limits may be relaxed to increase the performance of the engine and overall survivability of the aircraft; this comes at the cost of additional risk of an engine failure. The MBEC architecture offers the advantage of estimating key engine parameters that are not directly measureable. Estimating the unknown parameters allows for tighter control over these parameters, and on the level of risk the engine will operate at. This will allow the engine to achieve better performance than possible when operating to more conservative limits on a related, measurable parameter.

engine control↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗