Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “engine optimization”

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.

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

At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Lightweight Thrust Chamber Assemblies using Multi-Alloy Additive Manufacturing and Composite Overwrap

Additive Manufacturing (AM) has brought significant design and fabrication opportunities for complex components with internal features such as liquid rocket engine thrust chambers not previously possible. This technology allows for significant cost savings and schedule reductions in addition to new performance optimization through weight reduction and increased margins. Specific to regeneratively-cooled combustion chambers and nozzles for liquid rocket engines, additive manufacturing offers the ability to form the complex internal coolant channels and the closeout of the channels to contain the high pressure liquid propellants with a single operation. Much of additive manufacturing development has focused on monolithic alloys using Laser Powder Bed Fusion (L-PBF), which do not allow for complete optimization of the structure. The National Aeronautics and Space Administration (NASA) completed feasibility of an AM bimetallic L-PBF GRCop-84 copper-alloy combustion chamber with an AM electron beam freeform Inconel 625 structural jacket under the Low Cost Upper Stage Propulsion (LCUSP) Project. A follow-on project called Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) is under development to further expand large-scale multi-alloy thrust chambers while maturing composite overwrap technology for significant weight savings opportunities. The RAMPT project has three primary objectives: 1) Advancing blown powder Directed Energy Deposition (DED) to fabricate integral-channel large scale nozzles, 2) Develop composite overwrap technology to reduce weight and provide structural capability for thrust chamber assemblies, and 3) Develop bimetallic and multi-metallic additively manufactured radial and axial joints to optimize material performance. In addition to these primary manufacturing developments, analytical modeling efforts compliment the process development to simulate the AM processes to reduce build failures and distortions. The RAMPT project is also maturing the supply chain for various manufacturing processes described above in addition to L-PBF of GRCop-42. This paper will present an overview of the RAMPT project, the process development and hardware progress to date, material and hot-fire testing results, along with future developments.

Additive Manufacturing↗
DOE OSTI2022

A Two-Step Control Approach for Torque Ripple and Vibration Reduction in Switched Reluctance Motor Drives

The objective of this work is to reduce the torque ripple and vibration in Switched Reluctance Motor (SRM) drives. To achieve such a goal, a two-step approach is proposed. In the first step, the reference current is profiled using an optimization method, aimed to reduce the torque pulsation. In the second, the optimum current profile is applied to the SRM through an adaptive hysteresis band controller to actively cancel the radial vibration. The proposed technique uses an optimization procedure based on the Field Reconstruction Method (FRM) and Non-Derivative Optimization Method to find the optimal current profile that mitigates the torque pulsation, however, the investigation has shown that the proposed excitation leads to a higher radial vibration, which has been mitigated by using an adaptive hysteresis band controller. The theoretical basis for the proposed approach is initially presented, followed by system modeling and simulation. In addition, experimental verification has been conducted using an 8/6 SRM to show the feasibility of the proposed approach. The proposed method alleviates the acoustic noise and torque pulsation in SRM and offers an effective step towards the prevalent use of SRM in a wide range of applications.

42 ENGINEERING↗
NASA NTRS2015

A Framework for Orbital Performance Evaluation in Distributed Space Missions for Earth Observation

Distributed Space Missions (DSMs) are gaining momentum in their application to earth science missions owing to their unique ability to increase observation sampling in spatial, spectral and temporal dimensions simultaneously. DSM architectures have a large number of design variables and since they are expected to increase mission flexibility, scalability, evolvability and robustness, their design is a complex problem with many variables and objectives affecting performance. There are very few open-access tools available to explore the tradespace of variables which allow performance assessment and are easy to plug into science goals, and therefore select the most optimal design. This paper presents a software tool developed on the MATLAB engine interfacing with STK, for DSM orbit design and selection. It is capable of generating thousands of homogeneous constellation or formation flight architectures based on pre-defined design variable ranges and sizing those architectures in terms of predefined performance metrics. The metrics can be input into observing system simulation experiments, as available from the science teams, allowing dynamic coupling of science and engineering designs. Design variables include but are not restricted to constellation type, formation flight type, FOV of instrument, altitude and inclination of chief orbits, differential orbital elements, leader satellites, latitudes or regions of interest, planes and satellite numbers. Intermediate performance metrics include angular coverage, number of accesses, revisit coverage, access deterioration over time at every point of the Earth's grid. The orbit design process can be streamlined and variables more bounded along the way, owing to the availability of low fidelity and low complexity models such as corrected HCW equations up to high precision STK models with J2 and drag. The tool can thus help any scientist or program manager select pre-Phase A, Pareto optimal DSM designs for a variety of science goals without having to delve into the details of the engineering design process.

Earth Science↗
DOE OSTI2021

Plastic work constrained elastoplastic topology optimization

An elastoplastic topology optimization framework for limiting plastic work generation while maximizing stiffness is presented. The kinematics and constitutive model are based on finite strain linear isotropic hardening plasticity, and the balance laws are solved using a total Lagrangian finite element formulation. Aggregation of the specific plastic work combined with an adaptive normalization scheme efficiently constrains the maximum specific plastic work. The optimization problem is regularized using an augmented partial differential equation filter, and is solved by the method of moving asymptotes where path-dependent sensitivities are derived using the adjoint method. The numerical examples show a clear dependence on the optimized maximum stiffness structures for different levels of constrained specific plastic work. It is also shown that due to the history dependency of the plasticity, the load path significantly influences the structural performance and optimized topology.

42 ENGINEERING↗
NASA NTRS1976

EDIN design study alternate space shuttle booster replacement concepts. Volume 1: Engineering analysis

The use of a recoverable liquid rocket booster (LRB) system to replace the existing solid rocket booster (SRB) system for the shuttle was studied. Historical weight estimating relationships were developed for the LRB using Saturn technology and modified as required. Mission performance was computed using February 1975 shuttle configuration groundrules to allow reasonable comparison of the existing shuttle with the study designs. The launch trajectory was constrained to pass through both the RTLS/AOA and main engine cut off points of the shuttle reference mission 1. Performance analysis is based on a point design trajectory model which optimizes initial tilt rate and exoatmospheric pitch profile. A gravity turn was employed during the boost phase in place of the shuttle angle of attack profile. Engine throttling add/or shutdown was used to constrain dynamic pressure and/or longitudinal acceleration where necessary. Four basic configurations were investigated: a parallel burn vehicle with an F-1 engine powered LRB; a parallel burn vehicle with a high pressure engine powered LRB; a series burn vehicle with a high pressure engine powered LRB. The relative sizes of the LRB and the ET are optimized to minimize GLOW in most cases.

Demakes, P. T.↗
NASA NTRS1984

NASA Orbit Transfer Rocket Engine Technology Program

The advanced expander cycle engine with a 15,000 lb thrust level and a 6:1 mixture ratio and optimized performance was used as the baseline for a design study of the hydrogen/oxgyen propulsion system for the orbit transfer vehicle. The critical components of this engine are the thrust chamber, the turbomachinery, the extendible nozzle system, and the engine throttling system. Turbomachinery technology is examined for gears, bearing, seals, and rapid solidification rate turbopump shafts. Continuous throttling concepts are discussed. Components of the OTV engine described include the thrust chamber/nozzle assembly design, nozzles, the hydrogen regenerator, the gaseous oxygen heat exchanger, turbopumps, and the engine control valves.

Source record↗
NASA NTRS2024

Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Partial Hybrid Powertrain

The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept jet transport aircraft with a 2040 entry-into-service date. It utilizes electrified aircraft propulsion (EAP) to enable propulsive and aerodynamic benefits to reduce fuel usage, emissions, and cost. The powertrain consists of a single thrust producing, boundary layer-ingesting (BLI) turbofan gas turbine engine (GTE) with generators driving a series/parallel partial hybrid EAP system. The architecture includes 16 underwing contrarotating BLI fans, eight on each side, in a mailslot configuration. The 16 fans run on power extracted from the GTE through four 5 MW motor/generators connected to the Low-Pressure Spool, and a single 1 MW motor/generator on the High-Pressure Spool. The distributed fans can be used by the flight control to augment or replace the rudder function. At top of climb, the power extracted from the GTE for the fans is boosted by batteries. The design provides redundancy, and the capacity for boost means that the fans are designed to be able to provide additional thrust when necessary. These features can be leveraged in case of a fan or generator failure. This paper sets up the optimal control problem of setpoint determination for individual fans in the distributed propulsion system, accounting for electrical string efficiencies, saturations, and failures. The solution minimizes power consumption while maintaining thrust and torque on the airframe for maneuvering. Additionally, thrust that would have been lost due to temporary fan speed or power saturation is optimally redistributed to maintain overall desired thrust and torque on the aircraft. The power extraction range constraints derive from the gas turbine engine design and the small amount of variation allowed for the engine to maintain operability. The problem formulation allows the number and location of fan failures for which the thrust and torque can be maintained to be investigated, which has implications for certification. Simulations of a coordinated turn utilizing the distributed electric propulsion for yaw rate control under different failure scenarios demonstrate the robustness of the powertrain design to failures and help define its limitations.

Distributed Electric Propulsion↗
NASA NTRS1994

Hot-Gas-Slide and Coolant-Side Heat Transfer in Liquid Rocket Engine Combustors

The objectives of this article are to develop a multidisciplinary, computational methodology to predict the hot-gas-side and coolant-side heat transfer in film cooling assisted, regeneratively cooled liquid rocket engine combustors, and to use it in parametric studies to recommend optimized design of the coolant channels for a developmental combustor. An integrated numerical model which incorporates computational fluid dynamics (CFD) for the hot-gas thermal environment, and thermal analysis for the liner and coolant channels, was developed. This integrated CFD/thermal model was validated by comparing predicted heat fluxes with those of hot-firing test and industrial design methods for a 40-k calorimeter thrust chamber and the Space Shuttle Main Engine main combustion chamber. Parametric studies were performed for the advanced main combustion chamber to find a strategy for a proposed coolant channel design.

Ten-see Wang↗
DOE OSTI2022

On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control

Here, we study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domain into a set of overlapping subdomains, and solves all subproblems defined over subdomains in parallel. The convergence is attained by updating primal-dual information at the boundaries of overlapping subdomains. We show that the algorithm exhibits local linear convergence, and that the convergence rate improves exponentially with the overlap size. We also establish global convergence results for a general quadratic programming, which enables the application of the Schwarz scheme inside second-order optimization algorithms (e.g., sequential quadratic programming). The theoretical foundation of our convergence analysis is a sensitivity result of nonlinear OCPs, which we call "exponential decay of sensitivity" (EDS). Intuitively, EDS states that the impact of perturbations at domain boundaries (i.e., initial and terminal time) on the solution decays exponentially as one moves into the domain. Here, we expand a previous analysis available in the literature by showing that EDS holds for both primal and dual solutions of nonlinear OCPs, under uniform second-order sufficient condition, controllability condition, and boundedness condition. We conduct experiments with a quadrotor motion planning problem and a partial differential equations (PDE) control problem to validate our theory, and show that the approach is significantly more efficient than alternating direction method of multipliers and as efficient as the centralized interior-point solver.

42 ENGINEERING↗
DOE OSTI2024

Once-Through Steam Generator Model Analysis Using Python and Advanced Optimization Tools (Summer Internship Report)

This study focuses on the parametric analysis of design parameters for a once-through steam generator (OTSG) model, using python and advanced optimization tools to facilitate applications such as the flowing autoclave steam generator (FASG) test cases. Building on previous research involving another OTSG with a different design, this project aims to enhance our understanding of how steam generators (SGs) behave and how their outputs are influenced by changes in design. The reason for this design change is to allow for more precise modeling and optimization of SG performance, to provide a comparative analysis between the two designs, and to set up the model for integration with the FASG test case. The OTSG python-model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor-type small modular reactor system. Design studies involve changing the model’s input design parameters to observe the resulting effects on the output of the system. By using advanced optimization tools, such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory, detailed design parametric studies and model optimization were performed. Six input parameters—pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid), respectively, of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10% relative changes) for 600 samples. The analysis provides valuable insights into SG optimization and can be used for sensor placement optimization to effectively monitor and obtain experimental data in other tests.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗
DOE OSTI2025

Nonlinear programming optimization of a single-stack electrodialysis desalination system for cost efficiency

Electrodialysis (ED) presents a competitive method for desalinating brackish waters. In this work, we perform cost optimization of a single-stack ED system across a range of feed salinities and water recoveries while optimizing operating voltage, number of cell pairs, and cell length. The results of our optimization show that the levelized cost of water (LCOW) increases with an increase in feed salinity. The outcomes of our optimization show that cost-optimal design generally increases cell length while decreasing cell pair number and operating voltage with an increase in salinity. These trends are nonlinear, with the number of cell pairs and applied voltage exhibiting local maxima when operating at low salinity and high recovery. We discuss the underlying mechanism for cell length becoming a leveraging design parameter by inspecting the length-dependent profiles of key electrochemical properties of the ED cell. Finally, we present how increasing performance metrics and decreasing costs impact LCOW, demonstrating that innovations that decrease counter-current diffusion have resulted in the highest decrease of LCOW.

42 ENGINEERING↗
NASA NTRS1998

Nonlinear Control of a Reusable Rocket Engine for Life Extension

This paper presents the conceptual development of a life-extending control system where the objective is to achieve high performance and structural durability of the plant. A life-extending controller is designed for a reusable rocket engine via damage mitigation in both the fuel (H2) and oxidizer (O2) turbines while achieving high performance for transient responses of the combustion chamber pressure and the O2/H2 mixture ratio. The design procedure makes use of a combination of linear and nonlinear controller synthesis techniques and also allows adaptation of the life-extending controller module to augment a conventional performance controller of the rocket engine. The nonlinear aspect of the design is achieved using non-linear parameter optimization of a prescribed control structure. Fatigue damage in fuel and oxidizer turbine blades is primarily caused by stress cycling during start-up, shutdown, and transient operations of a rocket engine. Fatigue damage in the turbine blades is one of the most serious causes for engine failure.

Lorenzo, Carl F.↗
DOE OSTI2023

Computational design of metamaterials with self contact

Inverse homogenization in combination with contact modeling, topology optimization and shape optimization is used to design metamaterials with optimized macroscopic response. The homogenization assumes length scale separation which allows the non-linear macroscopic behavior to be obtained by analyzing a single unit cell in a lattice structure. Self contact in the unit cell, which is modeled using a third medium contact method, is leveraged to obtain a complex homogenized response. The inverse homogenization problem is initially formulated as a topology optimization problem, where the macroscopic stress–strain behavior is tuned to our liking. However, it is well known that boundary phenomena are difficult to model in topology optimization and that interface modeling is crucial to accurately analyze contact. For that reason, the boundary representation of the topology optimized design is extracted and used as initial design in a subsequent shape optimization. The behaviors of our designs are verified by performing rigorous post-processing analyzes using conforming meshes and conventional contact formulations.

42 ENGINEERING↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

PDE-constrained high-order mesh optimization

Here, we present a novel framework for PDE-constrained r-adaptivity of high-order meshes. The proposed method formulates mesh movement as an optimization problem, with an objective function defined as a convex combination of a mesh quality metric and a measure of the accuracy of the PDE solution obtained via finite element discretization. The proposed formulation achieves optimized, well-defined high-order meshes by integrating mesh quality control, PDE solution accuracy, and robust gradient regularization. We adopt the Target-Matrix Optimization Paradigm to control geometric properties across the mesh, independent of the PDE of interest. To incorporate the accuracy of the PDE solution, we introduce error measures that control the finite element discretization error. The implicit dependence of these error measures on the mesh nodal positions is accurately captured by adjoint sensitivity analysis. Additionally, a convolution-based gradient regularization strategy is used to ensure stable and effective adaptation of high-order meshes. We demonstrate that the proposed framework can improve mesh quality and reduce the error by up to 10 times for the solution of Poisson and linear elasto-static problems. The approach is general with respect to the dimensionality, the order of the mesh, the types of mesh elements, and can be applied to any PDE that admits well-defined adjoint operators.

Computer science↗