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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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NASA NTRS1990

Control-oriented modeling of combustion and flow processes in liquid propellant rocket engines

This paper presents a control-oriented model of the flow, reaction, and transport processes in liquid propellant rocket combustion chambers, based on the multicomponent conservation laws of gas dynamics. This model provides a framework for the inclusion of detailed chemical kinetic relations, viscous and other dissipative effects, a variety of actuators and sensors, as well as process and measurement disturbances. In addition to its potential usefulness to the designer in understanding the dynamical complexity of the system and the sources of model uncertainty, the model provides a rigorous basis for control system design. An appraisal of current and feasible actuators and sensors, and their mathematical representation are included.

Bentsman, Joseph↗

NASA NTRS2024

Influence of Ductility on the Performance of Lunar Habitat Structures Under Recurrent Disturbances

This research examines how ductility affects the durability of lunar surface structures against recurring disturbances like moonquakes, micrometeorite impacts, and thermal cycles over an extended period. The structural performance at various levels of ductility was determined by adjusting material parameters and the thickness of a reference multilayered dome structure. Moonquake and micrometeorite impact-induced lateral displacements were estimated using a reduced-order model under a control-oriented dynamic computational modeling framework. The study considered the degradation of the metallic dome’s strength properties over time due to thermal cycles. Fragility curves were generated by assessing the likelihood of reaching three predefined damage levels as a result of multiple hazards. Additionally, a discounted cash flow analysis was conducted to incorporate a financial aspect into the performance comparison. The findings revealed that structures with sufficient ductility capacity have a lower probability of sustaining severe damage or collapsing within a shorter time frame. Hence, having ductile structures in lunar environments is advantageous as it allows the postponement of maintenance and repair actions, thereby conserving scarce resources for more urgent tasks. Moreover, the financial analysis demonstrated that lunar habitats with higher ductile capacities result in larger net present values, offering a higher return on the initial investment.

Arsalan Majlesi↗

NASA NTRS2024

A Computational Framework for Making Early Design Decisions in Deep Space Habitats

The dynamics of systems of systems often involve complex interactions among the individual systems, making the implications of design choices challenging to predict. Design features in such systems may trigger unexpected behaviors or result in large variations in safety, performance or resilience. To provide a means of simulating such systems for aiding in these decisions, we have developed a prototype tool, the control-oriented dynamic computational modeling tool (CDCM). The CDCM provides rapid simulation capabilities to perform trade studies in systems of systems. The general class of systems of systems that we aim to examine involve multiple hazards, damage, cascading consequences, repair and recovery. We especially focus on systems-of-systems that incorporate a health management system (HMS) that can monitor the state of the habitat and make decisions about actions to take. In this paper we describe the features of the CDCM, the architecture we devised for simulation of systems-of-systems, the unique functionalities of this tool, and we provide a demonstration of the capabilities by performing two illustrative examples. We articulate the use of this tool for making early design decisions and demonstrate its use for trade studies that consider a model of a deep space habitat. We also share some experiences and lessons that may be useful for others seeking to address similar problems.

Amir Behjat↗

NASA NTRS2024

A Koopman-based residual modeling approach for the control of a soft robot arm

Soft robots are challenging to model and control due to their poorly defined kinematics and nonlinear dynamics. Recently, Koopman operator theory has been shown capable of constructing control-oriented soft robot models from data. However, building these models requires extensive data collection and they do not necessarily generalize well outside of the training observations. This paper presents a more data-efficient and generalizable approach to soft robot modeling that first identifies a physics-based Koopman model then supplements it with a data-driven residual Koopman model. The resulting combined model is linear and thus compatible with real-time model-based control techniques such as Model Predictive Control (MPC). The efficacy of the approach is demonstrated on several simulated systems and on a real soft robot arm, where it is shown to generate models that are more accurate than purely physics-based models and require less data to construct than purely data-driven models. Using a model-based controller, the soft arm is able to successfully track end effector trajectories, perform a pick-and-place task, and write on a dry-erase board, showcasing the applicability of this framework to increase the capabilities of soft robotic systems.

Daniel Bruder↗