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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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In this paper, we propose a two-fold approach to overcome the two limitations to the practical application of fault diagnosis of spacecraft and to develop a new and powerful diagnosis engine.
Saturn systems field acoustic data are used to derive mid- and far-field prediction parameters for rocket engine noise. The data were obtained during Saturn vehicle launches at the Kennedy Space Center. The data base is a sorted set of acoustic data measured during the period 1961 through 1971 for Saturn system launches SA-1 through AS-509. The model assumes hemispherical radiation from a simple source located at the intersection of the longitudinal axis of each booster and the engine exit plane. The model parameters are evaluated only during vehicle holddown. The acoustic normalized power spectrum and efficiency for each system are isolated as a composite from the data using linear numerical methods. The specific definitions of each allows separation. The resulting power spectra are nondimensionalized as a function of rocket engine parameters. The nondimensional Saturn system acoustic spectrum and efficiencies are compared as a function of Strouhal number with power spectra from other systems.
Advances in computational technology and in physics-based modeling are making large-scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze major propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of designing systems, providing the designer with critical information about the components early in the design process. This paper describes the development of the numerical propulsion system simulation (NPSS), a modular and extensible framework for the integration of multicomponent and multidisciplinary analysis tools using geographically distributed resources such as computing platforms, data bases, and people. The analysis is currently focused on large-scale modeling of complete aircraft engines. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.
Rhodococcus opacus is a non-model bacterium that is well suited for valorizing lignin. Despite recent advances in our systems-level understanding of its versatile metabolism, studies of its gene functions at a single gene level are still lagging. Elucidating gene functions in non-model organisms is challenging due to limited genetic engineering tools that are convenient to use. To address this issue, we developed a simple gene repression system based on CRISPR interference (CRISPRi). This gene repression system uses a T 7 RNA polymerase system to express a small guide RNA, demonstrating improved repression compared to the previously demonstrated CRISPRi system (i.e., the maximum repression efficiency improved from 58% to 85%). Additionally, our cloning strategy allows for building multiple CRISPRi plasmids in parallel without any PCR step, facilitating the engineering of this GC-rich organism. Using the improved CRISPRi system, we confirmed the annotated roles of four metabolic pathway genes, which had been identified by our previous transcriptomic analysis to be related to the consumption of benzoate, vanillate, catechol, and acetate. Furthermore, we showed our tool’s utility by demonstrating the inducible accumulation of muconate that is a precursor of adipic acid, an important monomer for nylon production. While the maximum muconate yield obtained using our tool was 30% of the yield obtained using gene knockout, our tool showed its inducibility and partial repressibility. In conclusion, our CRISPRi tool will be useful to facilitate functional studies of this non-model organism and engineer this promising microbial chassis for lignin valorization.
The combustion of middle distillates (diesel and jet fuel) is responsible for the emission of more than 2 GTon of CO 2 per year worldwide. While sustainable alternatives exist for gasoline and jet fuel, we still lack sustainable alternatives for diesel. This fact is especially relevant if we consider that electrification of sectors where diesel is used is challenging. One sustainable approach for diesel production is the catalytic upgrading of ethanol. While most work in this field has focused on the dehydration/oligomerization of ethanol, this approach is limited to producing fuels that have a high degree of branching and low cetane number. Another approach is the sequential use of ethanol Guerbet coupling, leading to higher alcohols, followed by etherification, leading to large ethers which, importantly, result in a product with high cetane number. In this work, we explore the catalytic upgrading of ethanol into diesel following an approach based on the initial Guerbet coupling of ethanol followed by etherification. The results presented are a collaborative and synergic effort among process and systems engineers, experimentalist in the area of catalysis, and fuel property modelers. Here, we demonstrate experimentally the feasibility of upgrading ethanol into a diesel fuel with properties that surpass its fossil counterpart. The diesel produced has a predicted cetane number of ~70 and outstanding cold flow properties, while maintaining other properties (viscosity, density, and flash point) within expected ranges. A technoeconomic analysis performed based on a detailed biorefinery model shows that the MFSP is ~5.89$ per Gal in 2021 dollars when lignocellulosic ethanol is used, with the most relevant economic driver the cost of the ethanol feedstock. The upgrading process can be performed with a net energy gain (EROI = 1.49 > 1). An LCA analysis of greenhouse gas (GHG) emissions reveals that the use of lignocellulosic ethanol may lead to more than 50% reduction in GHG emissions compared to fossil diesel. Depending on the CO 2 emissions associated with the production of ethanol we show that in some instances the production of carbon neutral diesel fuel is possible.
The requirements for a ground based manned controlled ecological life support system demonstration are summarized for the following: nutrition and food processing, food production, waste processing, systems engineering and modeling, and ecology-systems safety.
A technology program aimed at improving the performance of low thrust chemical rockets for spacecraft onboard applications is reviewed. Navier-Stokes analyses of low Reynolds number rocket flows have been compared with local flow property measurements obtained using Rayleigh and Raman diagnostics in a 100 N gaseous hydrogen/gaseous oxygen rocket. It is indicated that computational domain should include the near injector flow and that the shear layer combustion model needs improvement. The system analyses and technical efforts intended to develop a technology base for higher performance propellants are presented. A LOX/hydrazine engine is demonstrated to have a 95 percent theoretical c-star which translates into a projected vacuum specific impulse of 345 seconds at an area ratio of 204:1.
This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.
CATTENS is a model-based, multi disciplinary concurrent engineering tool whose purpose is to enable engineers and scientists to collaborate in defining and developing a mission or system concept. The initial deployment target for CATTENS is the GSFC Mission Design Laboratory (MDL), but CATTENS is available to all GSFC engineers and scientists.
NASA aims to deploy a fission reactor on the lunar surface by 2030 to generate 100 kWe of power for at least 10 years without maintenance or refueling. To assess system and subsystem survivability according to those requirements, a model of the reactor pallet was created in the radiation transport code MCNP to determine the neutron fluences and gamma doses that the materials and systems would be exposed to. The model was based on the 2025 government design. The model indicated that the control drum motors, Brayton cycle engines, and pipes and valves would be exposed to neutron fluences of 1×10 15 – 1×10 16 n/cm 2 per year and gamma doses ranging from 10 to 500 Mrad per year. The electronics box housing the instrumentation and control elements is expected to receive 1×10 14 – 1×10 15 n/cm 2 per year and gamma doses in the range of 1–5 Mrad per year. These doses necessitate that the control drum motors, Brayton cycle engines, valve components, control electronics, and other components be radiation-hardened (>10 16 n/cm 2 and >10 Mrad gamma dose) or additionally shielded to survive the 10-year lunar mission.
Residential buildings’ heating and cooling loads are associated with significant carbon emissions and peak electricity demand. Phase change material (PCM) based thermal energy storage (TES) can be used for space heating and cooling by embedding into the heat pump equipment. Past work on TES integrated with heat pumps (HP) has demonstrated significant load shifting and economic benefits. However, the potential for TES to reduce carbon emissions has not been widely explored. This study evaluates carbon mitigation potential of an ice-based TES coupled to HP (HP-TES) based on a simple rule-based control strategy accounting for electric grid emissions data. A vapor compression HP model using Engineering Equation Solver (EES). The modeled HP-TES system for single-family residential building demonstrates decreased carbon emissions with reduced peak utility cost.
Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.
The Controls and Dynamics Technology Branch at NASA Glenn Research Center are interested in combining a solid oxide fuel cell (SOFC) to operate in conjunction with a gas turbine engine. A detailed engine model currently exists in the Matlab/Simulink environment. The idea is to incorporate a SOFC model within the turbine engine simulation and observe the hybrid system's performance. The fuel cell will be heated to its appropriate operating condition by the engine s combustor. Once the fuel cell is operating at its steady-state temperature, the gas burner will back down slowly until the engine is fully operating on the hot gases exhausted from the SOFC. The SOFC code is based on a steady-state model developed by The U.S. Department of Energy (DOE). In its current form, the DOE SOFC model exists in Microsoft Excel and uses Visual Basics to create an I-V (current-voltage) profile. For the project's application, the main issue with this model is that the gas path flow and fuel flow temperatures are used as input parameters instead of outputs. The objective is to create a SOFC model based on the DOE model that inputs the fuel cells flow rates and outputs temperature of the flow streams; therefore, creating a temperature profile as a function of fuel flow rate. This will be done by applying the First Law of Thermodynamics for a flow system to the fuel cell. Validation of this model will be done in two procedures. First, for a given flow rate the exit stream temperature will be calculated and compared to DOE SOFC temperature as a point comparison. Next, an I-V curve and temperature curve will be generated where the I-V curve will be compared with the DOE SOFC I-V curve. Matching I-V curves will suggest validation of the temperature curve because voltage is a function of temperature. Once the temperature profile is created and validated, the model will then be placed into the turbine engine simulation for system analysis.
“Charge engineering” of semiconductor nanocrystals (NCs) through so-called electronic impurity doping is a long-standing challenge in colloidal chemistry and holds promise for ground-breaking advancements in many optoelectronic, photonic, and spin-based nanotechnologies. To date, our knowledge is limited to a few paradigmatic studies on a small number of model compounds and doping conditions, with important electronic dopants still unexplored in nanoscale systems. Equally importantly, fine-tuning of charge engineered NCs is hampered by the statistical limitations of traditional approaches. The resulting intrinsic doping inhomogeneity restricts fundamental studies to statistically averaged behaviors and complicates the realization of advanced device concepts based on their advantageous functionalities. We aim to address these issues by realizing the first example of II–VI NCs electronically doped with an exact number of heterovalent gold atoms, a known p-type acceptor impurity in bulk chalcogenides. Single-dopant accuracy across entire NC ensembles is obtained through a novel non-injection synthesis employing ligand-exchanged gold clusters as “quantized” dopant sources to seed the nucleation of CdSe NCs in organic media. Structural, spectroscopic, and magneto-optical investigations trace a comprehensive picture of the physical processes resulting from the exact doping level of the NCs. Gold atoms, doped here for the first time into II–VI NCs, are found to incorporate as nonmagnetic Au + species activating intense size-tunable intragap photoluminescence and artificially offsetting the hole occupancy of valence band states. Fundamentally, the transient conversion of Au + to paramagnetic Au 2+ (5d 9 configuration) under optical excitation results in strong photoinduced magnetism and diluted magnetic semiconductor behavior revealing the contribution of individual paramagnetic impurities to the macroscopic magnetism of the NCs. Altogether, our results demonstrate a new chemical approach toward NCs with physical functionalities tailored to the single impurity level and offer a versatile platform for future investigations and device exploitation of individual and collective impurity processes in quantum confined structures.
Thermal engineering has long been left out of the concurrent engineering environment dominated by CAD (computer aided design) and FEM (finite element method) software. Current tools attempt to force the thermal design process into an environment primarily created to support structural analysis, which results in inappropriate thermal models. As a result, many thermal engineers either build models "by hand" or use geometric user interfaces that are separate from and have little useful connection, if any, to CAD and FEM systems. This paper describes the development of a new thermal design environment called the Thermal Desktop. This system, while fully integrated into a neutral, low cost CAD system, and which utilizes both FEM and FD methods, does not compromise the needs of the thermal engineer. Rather, the features needed for concurrent thermal analysis are specifically addressed by combining traditional parametric surface based radiation and FD based conduction modeling with CAD and FEM methods. The use of flexible and familiar temperature solvers such as SINDA/FLUINT (Systems Improved Numerical Differencing Analyzer/Fluid Integrator) is retained.
A document describes the Antenna Calibration & Measurement Equipment (ACME) system that will provide the Deep Space Network (DSN) with instrumentation enabling a trained RF engineer at each complex to perform antenna calibration measurements and to generate antenna calibration data. This data includes continuous-scan auto-bore-based data acquisition with all-sky data gathering in support of 4th order pointing model generation requirements. Other data includes antenna subreflector focus, system noise temperature and tipping curves, antenna efficiency, reports system linearity, and instrument calibration. The ACME system design is based on the on-the-fly (OTF) mapping technique and architecture. ACME has contributed to the improved RF performance of the DSN by approximately a factor of two. It improved the pointing performances of the DSN antennas and productivity of its personnel and calibration engineers.
This paper presents the objectives-driven, case-based safety and mission success (S&MS) assurance framework being developed by the NASA Office of Safety and Mission Assurance (OSMA), including its motivations and its implementation via a S&MS Assurance Standard that is under development, supplemented by supporting standards including an S&MS Analysis Management Standard that is also under development. A need to evolve NASA’s S&MS assurance framework has emerged in recent years, resulting from the need to accommodate new acquisition models; the need to accommodate evolving systems engineering (SE) practices; the need to stipulate acceptable levels of S&MS risk; the need for improved integration of S&MS into SE; and the need for clearer risk acceptance accountability. The objectives-driven, case-based S&MS assurance framework proposed here is responsive to that need. Its key features include: • The establishment, by NASA Acquirers, of fundamental S&MS performance objectives that define limits of acceptability for the likelihoods that mission technical objectives will be accomplished and that people, assets, and environments put at risk by the mission will not be adversely affected; • The development and approval of Providers’ S&MS plans for meeting Acquirers’ S&MS performance objectives, including commitments to support Acquirer audit, investigation, and reporting needs; • The development, by Providers, of S&MS assurance cases that argue, supported by evidence, that the Provider has met, or is on track to meeting, the fundamental S&MS objectives; • The evaluation, throughout the program/project life cycle, of Provider S&MS assurance cases as the primary S&MS-related technical basis for Acquirer risk acceptance and the granting to the Provider of authority to proceed through the program/project life cycle. This proposed S&MS assurance framework is notable for its lack of prescription of traditional S&MS requirements and strategies such as defined failure tolerances, margins, or analysis requirements. Instead, Providers are given latitude to propose their own strategies for meeting the fundamental S&MS performance objectives, subject to independent review and Acquirer approval. The result is a framework for S&MS assurance that is at once both rigorous and flexible.
Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.