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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 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Some Interesting Applications of Probabilistic Techiques in Structural Dynamic Analysis of Rocket Engines

Numerical and Analytical methods developed to determine damage accumulation in specific engine components when speed variation included. Dither Life Ratio shown to be well over factor of 2 for specific example. Steady‐State assumption shown to be accurate for most turbopump cases, allowing rapid calculation of DLR. If hot‐fire speed data unknown, Monte Carlo method developed that uses speed statistics for similar engines. Application of techniques allow analyst to reduce both uncertainty and excess conservatism. High values of DLR could allow previously unacceptable part to pass HCF criteria without redesign. Given benefit and ease of implementation, recommend that any finite life turbomachine component analysis adopt these techniques. Probability Values calculated, compared, and evaluated for several industry‐proposed methods for combining random and harmonic loads. Two new excel macros written to calculate combined load for any specific probability level. Closed form Curve fits generated for widely used 3(sigma) and 2(sigma) probability levels. For design of lightweight aerospace components, obtaining accurate, reproducible, statistically meaningful answer critical.

Brown, Andrew M.↗

DOE OSTI2022

Cas9-Based Metabolic Engineering of Issatchenkia orientalis for Enhanced Utilization of Cellulosic Hydrolysates

Issatchenkia orientalis, exhibiting high tolerance against harsh environmental conditions, is a promising metabolic engineering host for producing fuels and chemicals from cellulosic hydrolysates containing fermentation inhibitors under acidic conditions. Although genetic tools for I. orientalis exist, they require auxotrophic mutants so that the selection of a host strain is limited. We developed a drug resistance gene (cloNAT)-based genome-editing method for engineering any I. orientalis strains and engineered I. orientalis strains isolated from various sources for xylose fermentation. Specifically, xylose reductase, xylitol dehydrogenase, and xylulokinase from Scheffersomyces stipitis were integrated into an intended chromosomal locus in four I. orientalis strains (SD108, IO21, IO45, and IO46) through Cas9-based genome editing. Furthermore, the resulting strains (SD108X, IO21X, IO45X, and IO46X) efficiently produced ethanol from cellulosic and hemicellulosic hydrolysates even though the pH adjustment and nitrogen source were not provided. As they presented different fermenting capacities, selection of a host I. orientalis strain was crucial for producing fuels and chemicals using cellulosic hydrolysates.

09 BIOMASS FUELS↗

NASA NTRS1981

Experimental analysis of IMEP in a rotary combustion engine

A real time indicated mean effective pressure measurement system is described which is used to judge proposed improvements in cycle efficiency of a rotary combustion engine. This is the first self-contained instrument that is capable of making real time measurements of IMEP in a rotary engine. Previous methods used require data recording and later processing using a digital computer. The unique features of this instrumentation include its ability to measure IMEP on a cycle by cycle, real time basis and the elimination of the need to differentiate volume function in real time. Measurements at two engine speeds (2000 and 3000 rpm) and a full range of loads are presented, although the instrument was designed to operate to speeds of 9000 rpm.

Schock, H. J.↗

NASA NTRS1981

Experimental analysis of IMEP in a rotary combustion engine

This experimental work demonstrates the use of a NASA designed, real time Indicated Mean Effective Pressure (IMEP) measurement system which will be used to judge proposed improvements in cycle efficiency of a rotary combustion engine. This is the first self-contained instrument that is capable of making real time measurements of IMEP in a rotary engine. Previous methods used require data recording and later processing using a digital computer. The unique features of this instrumentation include its ability to measure IMEP on a cycle by cycle, real time basis and the elimination of the need to differentiate the volume function in real time. Measurements at two engine speeds (2000 and 3000 RPM) and a full range of loads are presented, although the instrument was designed to operate to speeds of 9000 RPM.

Schock, H. J.↗

NASA NTRS2011

Towards a State Based Control Architecture for Large Telescopes: Laying a Foundation at the VLT

Large telescopes are characterized by a high level of distribution of control-related tasks and will feature diverse data flow patterns and large ranges of sampling frequencies; there will often be no single, fixed server-client relationship between the control tasks. the architecture is also challenged by the task of integrating heterogeneous subsystems which will be delivered by multiple different contractors. Due to the high number of distributed components, the control system needs to effectively detect errors and faults, impede their propagation, and accurately mitigate them in the shortest time possible, enabling the service to be restored. The presented Data-Driven Architecture is based on a decentralized approach with an end-to-end integration of disparate, independently developed software components. These components employ a high-performance standards-based communication middle-ware infrastructure, based on the Data Distribution Service. A set of rules and principles, based on JPL's State Analysis method and architecture, are use to constrain component-to component interactions, where the Control System and System Under Control are clearly separated. State Analysis provide a model-based process for capturing system and software requirements and design, greatly reducing the gap between the requirements on software specified by systems engineers and the implementation by software engineers. The method and architecture has been field tested at the Very Large Telescope, where it has been integrated into an operational system.

European Extremely Large Telescope (E-ELT)↗

NASA NTRSDate not supplied

Automation of the Uncertainty Quantification Process Based on Probability Boxes with DAKOTA

To date, while the use of CFD is prevalent, very few efforts have been undertaken that truly attempt to document all (or even most) of the sources of uncertainty in the simulations. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the design research and engineering community, test and evaluation community, and ultimately certification for flight. This is especially true for hypersonic air-breathing propulsion systems due to the environment, scale, and duration limitations of ground test facilities. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. Hence, a major obstacle that has prevented the adoption of UQ methods for engineering design and development work is the lack of a tool set to automate most (if not all) of the UQ workflow. Towards this end, the SANDIA package DAKOTA (which has been developed to drive both UQ and optimization processes) will be tightly wrapped around the VULCAN-CFD code to automate the uncertainty quantification process. The automated process will be applied to an isolator turbulence model validation exercise that has previously been documented using a manual approach to the UQ process. Hence, the focus of this paper will be documenting the level to which automation can hide the UQ process details from the CFD practitioner rather than the UQ method itself.

CFD↗

DOE OSTI2026

Vapor-phase pillarization of MXenes for engineering hierarchical interlayer porosity

MXenes, a family of two-dimensional (2D) multilamellar materials, possess excellent thermal and electronic properties for a range of applications. Their use in heterogeneous catalysis, however, is limited by the low surface area resulting from stacked layers. Pillarization with inorganic oxides can create more open, mesoporous MXene structures, improving accessibility for guest species to diffuse, reside or react in the space between 2D layers. A previous liquid-phase pillarization method, however, involves excessive use of solvent-based precursors and multiple processing steps. Here, we report a vapor-phase pillarization (VPP) strategy to introduce pillars, exemplified by silica pillars, with high pillar precursor usage efficiency and a simplified processing workflow. The resulting silica-pillared mesoporous MXene exhibits significantly increased surface area and porosity. These textural properties can be easily tuned by the VPP synthesis conditions. When applied as a ruthenium (Ru) catalyst support for the hydrogenolysis of low-density polyethylene (LDPE), the silica-pillared MXene enabled high Ru dispersion and catalytic activity. This study highlights the potential of the VPP method for engineering mesoporous, 2D MXene materials and demonstrates the effectiveness of mesoporous MXene as a catalyst support in overcoming mass transport and active-site accessibility challenges in heterogeneous catalysis involving bulky substances, such as plastics upcycling.

Luo, Song [University of Delaware, Newark, DE (Uni↗

DOE OSTI2023

Neural Network-Enhanced Reproducing Kernel Particle Method for Image-Based Multiphysics Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant stresses during charge/discharge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), image-based modeling techniques are used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electrochemical-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in capturing crack propagation due to mesh dependency. Additionally, commonly used damage models, such as the continuous damage model and the cohesive zone model, often have steep tradeoffs between discontinuous field accuracy and computational expense. In this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022.

damage modeling↗

NASA NTRS1966

Solid propellant rocket motor performance computer programs using the group transformation method

Solid propellant rocket engine performance computer programs using group transformation method

SOLID PROPELLANT ROCKET ENGINE↗

NASA NTRS2003

Launch Vehicle Design and Optimization Methods and Priority for the Advanced Engineering Environment

NASA's Advanced Engineering Environment (AEE) is a research and development program that will improve collaboration among design engineers for launch vehicle conceptual design and provide the infrastructure (methods and framework) necessary to enable that environment. In this paper, three major technical challenges facing the AEE program are identified, and three specific design problems are selected to demonstrate how advanced methods can improve current design activities. References are made to studies that demonstrate these design problems and methods, and these studies will provide the detailed information and check cases to support incorporation of these methods into the AEE. This paper provides background and terminology for discussing the launch vehicle conceptual design problem so that the diverse AEE user community can participate in prioritizing the AEE development effort.

Rowell, Lawrence F.↗

NASA NTRS1990

What can formal methods offer to digital flight control systems design

Formal methods research begins to produce methods which will enable mathematic modeling of the physical behavior of digital hardware and software systems. The development of these methods directly supports the NASA mission of increasing the scope and effectiveness of flight system modeling capabilities. The conventional, continuous mathematics that is used extensively in modeling flight systems is not adequate for accurate modeling of digital systems. Therefore, the current practice of digital flight control system design has not had the benefits of extensive mathematical modeling which are common in other parts of flight system engineering. Formal methods research shows that by using discrete mathematics, very accurate modeling of digital systems is possible. These discrete modeling methods will bring the traditional benefits of modeling to digital hardware and hardware design. Sound reasoning about accurate mathematical models of flight control systems can be an important part of reducing risk of unsafe flight control.

Good, Donald I.↗

NASA NTRS2001

Designing Extraterrestrial Plant Growth Habitats With Low Pressure Atmospheres

In-situ resource utilization, provision of human life support requirements by bioregenerative methods, and engineering constraints for construction and deployment of plant growth structures on the surface of Mars all suggest the need for plant growth studies at hypobaric pressures. Past work demonstrated that plants will likely tolerate and grow at pressures at or below 10 kPa. Based upon this premise, concepts are developed for the design of reduced pressure atmospheres in lightweight, inflatable structures for plant growth systems on Mars with the goals of maximizing design simplicity and the use of local resources. A modular pod design is proposed as it could be integrated with large-scale production systems. Atmospheric modification of pod clusters would be based upon a pulse and scrub system using mass flow methods for atmospheric transport. A specific modification and control scenario is developed for a lettuce pod to illustrate the dynamics of carbon dioxide and oxygen exchange within a pod. Considerations of minimal atmospheric crop requirements will aid in the development of engineering designs and strategies for extraterrestrial plant growth structures that employ rarefied atmospheres.

Corey, Kenneth A.↗

NASA NTRS2002

Designing Extraterrestrial Plant Growth Habitats with Low Pressure Atmospheres

Corey, Kenneth A.↗

NASA NTRS1999

Data Reduction Methods Applied to the Fastrac Engine

The Fastrac rocket engine is currently being developed for the X-34 technology demonstrator vehicle. The engine performance model must be calibrated to support accurate performance prediction. Data reduction is the process of estimating hardware characteristics from available test data, and is essential for effective performance model calibration and prediction. A new data reduction procedure was developed, implemented, and tested using data from Fastrac engine tests. The procedure selects hardware and test measurements to use in the reduction process based on examination of the model influence matrix condition number. Predicted hardware characteristics are recovered from the solution of a quadratic programming problem. Computational tests indicate that the new procedure provides a significant improvement in test data reduction capability. Enhancements include improved test data utilization and time history data reduction capability. The new method is generically applicable to other systems.

Santi, L. Michael↗

NASA NTRS2008

Computational Analyses in Support of Sub-scale Diffuser Testing for the A-3 Facility: Aero-Acoustic Analyses and Experimental Validation - Part 3

A unique assessment of acoustic similarity scaling laws and acoustic analogy methodologies in predicting the far-field acoustic signature from a sub-scale altitude rocket test facility at the NASA Stennis Space Center was performed. A directional, point-source similarity analysis was implemented for predicting the acoustic far-field. In this approach, experimental acoustic data obtained from "similar" rocket engine tests were appropriately scaled using key geometric and dynamic parameters. The accuracy of this engineering-level method is discussed by comparing the predictions with acoustic far-field measurements obtained. In addition, a CFD solver was coupled with a Lilley's acoustic analogy formulation to determine the improvement of using a physics-based methodology over an experimental correlation approach. In the current work, steady-state Reynolds-averaged Navier-Stokes calculations were used to model the internal flow of the rocket engine and altitude diffuser. These internal flow simulations provided the necessary realistic input conditions for external plume simulations. The CFD plume simulations were then used to provide the spatial turbulent noise source distributions in the acoustic analogy calculations. Preliminary findings of these studies will be discussed.

Allgood, Daniel C.↗

NASA NTRS1996

A General Interface Method for Aeroelastic Analysis of Aircraft

The aeroelastic analysis of an aircraft requires an accurate and efficient procedure to couple aerodynamics and structures. The procedure needs an interface method to bridge the gap between the aerodynamic and structural models in order to transform loads and displacements. Such an interface method is described in this report. This interface method transforms loads computed by any aerodynamic code to a structural finite element (FE) model and converts the displacements from the FE model to the aerodynamic model. The approach is based on FE technology in which virtual work is employed to transform the aerodynamic pressures into FE nodal forces. The displacements at the FE nodes are then converted back to aerodynamic grid points on the aircraft surface through the reciprocal theorem in structural engineering. The method allows both high and crude fidelities of both models and does not require an intermediate modeling. In addition, the method performs the conversion of loads and displacements directly between individual aerodynamic grid point and its corresponding structural finite element and, hence, is very efficient for large aircraft models. This report also describes the application of this aero-structure interface method to a simple wing and an MD-90 wing. The results show that the aeroelastic effect is very important. For the simple wing, both linear and nonlinear approaches are used. In the linear approach, the deformation of the structural model is considered small, and the loads from the deformed aerodynamic model are applied to the original geometry of the structure. In the nonlinear approach, the geometry of the structure and its stiffness matrix are updated in every iteration and the increments of loads from the previous iteration are applied to the new structural geometry in order to compute the displacement increments. Additional studies to apply the aero-structure interaction procedure to more complicated geometry will be conducted in the second phase of the present contract.

Tzong, T.↗

NASA NTRS2001

A Global Optimization Methodology for Rocket Propulsion Applications

While the response surface method is an effective method in engineering optimization, its accuracy is often affected by the use of limited amount of data points for model construction. In this chapter, the issues related to the accuracy of the RS approximations and possible ways of improving the RS model using appropriate treatments, including the iteratively re-weighted least square (IRLS) technique and the radial-basis neural networks, are investigated. A main interest is to identify ways to offer added capabilities for the RS method to be able to at least selectively improve the accuracy in regions of importance. An example is to target the high efficiency region of a fluid machinery design space so that the predictive power of the RS can be maximized when it matters most. Analytical models based on polynomials, with controlled level of noise, are used to assess the performance of these techniques.

Source record↗

DOE OSTI2023

Methods for generating barcoded combinatorial libraries

Provided herein are methods and composition for trackable genetic variant libraries. Further provided herein are methods and compositions for recursive engineering. Further provided herein are methods and compositions for multiplex engineering. Further provided herein are methods and compositions for enriching for editing and trackable engineered sequences and cells using nucleic acid-guided nucleases.

Gill, Ryan T.↗