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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 685 records · Page 38

Problem solving in a distributed environment

Distributed problem solving is anayzed as a blend of two disciplines: (1) problem solving and ai; and (2) distributed systems (monitoring). It may be necessary to distribute because the application itself is one of managing distributed resources (e.g., distributed sensor net) and communication delays preclude centralized processing, or it may be desirable to distribute because a single computational engine may not satisfy the needs of a given task. In addition, considerations of reliability may dictate distribution. Examples of multi-process language environment are given.

Rashid, R. F.↗

Finite-Element Methods for Real-Time Simulation of Surgery

Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.

Basdogan, Cagatay↗

Implementation of nonreflective boundary condition at the outflow boundary

Numerical techniques for the solution of free surface flows about a disturbance on or near a free surface were developed. Any disturbance moving on or near a liquid surface generates surface waves that propagate away from the disturbance. The potential flow problems in which the evolution of free surface waves is the principal phenomenon of interest are considered. The distinct feature of these problems is that the position of the surface is also unknown and is to be determined as part of the solution. Two boundary conditions are required at the free surface since there are two unknown functions there, the free surface height and the potential function. The required boundary conditions are satisfied by the kinematic condition which states that no flow can cross the surface and the dynamic condition which matches the fluid pressure to the pressure acting on the surface through Bernoulli's equation.

Hall, D. R.↗

A multiple scales approach to sound generation by vibrating bodies

The problem of determining the acoustic field in an inviscid, isentropic fluid generated by a solid body whose surface executes prescribed vibrations is formulated and solved as a multiple scales perturbation problem, using the Mach number M based on the maximum surface velocity as the perturbation parameter. Following the idea of multiple scales, new 'slow' spacial scales are introduced, which are defined as the usual physical spacial scale multiplied by powers of M. The governing nonlinear differential equations lead to a sequence of linear problems for the perturbation coefficient functions. However, it is shown that the higher order perturbation functions obtained in this manner will dominate the lower order solutions unless their dependence on the slow spacial scales is chosen in a certain manner. In particular, it is shown that the perturbation functions must satisfy an equation similar to Burgers' equation, with a slow spacial scale playing the role of the time-like variable. The method is illustrated by a simple one-dimenstional example, as well as by three different cases of a vibrating sphere. The results are compared with solutions obtained by purely numerical methods and some insights provided by the perturbation approach are discussed.

Geer, James F.↗

Invertible Neural Networks for Airfoil Design

We report the airfoil design problem, in which an engineer seeks a shape with desired performance characteristics, is fundamental to aerodynamics. Design workflows traditionally rely on iterative optimization methods using low-fidelity integral boundary-layer methods as higher-fidelity adjoint-based computational fluid dynamics methods are computationally expensive. Surrogate-based approaches can accelerate the design process but still rely on some iterative inverse design procedure. In this work, we leverage emerging invertible neural network (INN) tools to enable the rapid inverse design of airfoil shapes for wind turbines. INNs are specialized deep-learning models with well-defined inverse mappings. When trained appropriately, INN surrogate models are capable of forward prediction of aerodynamic and structural quantities for a given airfoil shape as well as inverse recovery of airfoil shapes with specified aerodynamic and structural characteristics. The INN approach offers a roughly 100 times speed-up compared to adjoint-based methods for inverse design. We demonstrate the INN tool for inverse design on three test cases of 100 airfoils each that satisfy the performance characteristics close to those of airfoils used in wind-turbine blades. All generated shapes satisfy the desired aerodynamic characteristics, demonstrating the success of the INN approach for inverse design of airfoils.

17 WIND ENERGY↗

Efficient proximal subproblem solvers for a nonsmooth trust-region method

In [R. J. Baraldi and D. P. Kouri, Mathematical Programming, (2022), pp. 1-40], we introduced an inexact trust-region algorithm for minimizing the sum of a smooth nonconvex and nonsmooth convex function. The principle expense of this method is in computing a trial iterate that satisfies the so-called fraction of Cauchy decrease condition—a bound that ensures the trial iterate produces sufficient decrease of the subproblem model. In this paper, we expound on various proximal trust-region subproblem solvers that generalize traditional trust-region methods for smooth unconstrained and convex-constrained problems. We introduce a simplified spectral proximal gradient solver, a truncated nonlinear conjugate gradient solver, and a dogleg method. Finally, we compare algorithm performance on examples from data science and PDE-constrained optimization.

97 MATHEMATICS AND COMPUTING↗

Minimum fuel horizontal flightpaths in the terminal area

The problem of minimum fuel airplane trajectories from arbitrary initial states to be fixed final state is considered. There are four state variables (two position coordinates, heading, and constrained velocity) and two constrained controls (thrust and bank angle). The fuel optimality of circular and straight line flightpaths is examined. Representative extremals (trajectories satisfying the necessary conditions of the minimum principle) of various types are computed and used to evaluate trajectories generated by an on line algorithm. Attention is paid to the existence of Darboux points (beyond which an extremal ceases to be globally optimal). One fuel flow rate model includes a term quadratic in thrust; hence, the optimal thrust is continuous and nonsingular. The other fuel flow rate model is linear in thrust, and consequently the optimal thrust is discontinuous and singular.

Kreindler, E.↗

Giant step for communication satellite technology

NASA's communications program, which is concerned with advanced communications technology, reflects the need for operational communications satellite capacity beyond the capabilities of current technology and the unwillingness of private industry in the U.S. to undertake making the required long-range, high-risk technology advances. It is pointed out that current satellites will not satisfy the forecasted demand for additional capacity in the 1990s and beyond. Current technology exists primarily up to 18 GHz. Designing a communications satellite at each of the three major uplink/downlink frequency bands (C, Ku, and Ka, 6/4 GHz, 14/11 GHz, and 30/20 GHz, respectively) presents different program management and technical problems. Increasing frequency or power can be done only by intensive sustained research. This is the rationale for NASA to pursue the Advanced Communications Technology Satellite (ACTS) program.

Lovell, R. R.↗

An infeasible-start framework for convex quadratic optimization, with application to constraint-reduced interior-point and other methods

A framework is proposed for solving general convex quadratic programs (CQPs) from an infeasible starting point by invoking an existing feasible-start algorithm tailored for inequality-constrained CQPs. The central tool is an exact penalty function scheme equipped with a penalty-parameter updating rule. The feasible-start algorithm merely has to satisfy certain general requirements, and so is the updating rule. Under mild assumptions, the framework is proved to converge on CQPs with both inequality and equality constraints and, at a negligible additional cost per iteration, produces an infeasibility certificate, together with a feasible point for an (approximately) ℓ 1 -least relaxed feasible problem, when the given problem does not have a feasible solution. The framework is applied to a feasible-start constraint-reduced interior-point algorithm previously proved to be highly performant on problems with many more inequality constraints than variables (“imbalanced”). Numerical comparison with popular codes (OSQP, qpOASES, MOSEK) is reported on both randomly generated problems and support-vector machine classifier training problems. The results show that the former typically outperforms the latter on imbalanced problems. Finally, application of the proposed infeasible-start framework to other feasible-start algorithms is briefly considered, and is tested on a simplex iteration.

97 MATHEMATICS AND COMPUTING↗

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗

Enhanced Power Grid Maintenance Planning and Quantum-Inspired Combinatorial Prospects

Efficient and reliable scheduling of maintenance for power generation and transmission infrastructure is essential for minimizing operational costs and ensuring grid stability. This paper introduces an integrated optimization framework for coordinated maintenance scheduling of generators and transmission lines under resource and reliability constraints. The model minimizes a composite cost function including maintenance and generation costs, as well as penalties for delayed maintenance, while satisfying N−1 security constraints, operational limits, and crew availability. Case studies on the IEEE 300-bus test system demonstrate the effectiveness of the proposed approach in producing feasible and cost-effective maintenance schedules. To address scalability and combinatorial complexity, the model is mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling exploration of solution approaches based on Quantum Imaginary Time Evolution (QITE). While the QUBO reformulation provides a foundation for future quantum-inspired optimization, this study focuses primarily on the development and demonstration of the classical optimization framework and illustrates the potential applicability of QITE in large-scale maintenance scheduling.

Chen, Yang [ORNL] (ORCID:0000000271693874)↗

Similarity constraints in testing of cooled engine parts

A study is made of the effect of testing cooled parts of current and advanced gas turbine engines at the reduced temperature and pressure conditions which maintain similarity with the engine environment. Some of the problems facing the experimentalist in evaluating heat transfer and aerodynamic performance when hardware is tested at conditions other than the actual engine environment are considered. Low temperature and pressure test environments can simulate the performance of actual size prototype engine hardware within the tolerance of experimental accuracy if appropriate similarity conditions are satisfied. Failure to adhere to these similarity constraints because of test facility limitations or other reasons, can result in a number of serious errors in projecting the performance of test hardware to engine conditions.

Colladay, R. S.↗

Aeroelastic stability of trimmed helicopter blades in forward flight

Equations for moderately large amplitude coupled flap-lag motion of a torsionally rigid hingeless elastic helicopter blade in forward flight are derived. Quasi-steady aerodynamic loads are considered and the effects of reversed flow are included. By using Galerkin's method the spatial dependence of the problem is eliminated and the equations are linearized about a time dependent equilibrium position determined from the trimmed equilibrium position of the rotor in forward flight. In the first trim procedure the rotor is maintained at a fixed value of thrust coefficient with forward flight and horizontal and vertical force equilibrium is satisfied in addition to maintaining zero pitch and roll moments. The second trim procedure maintains only zero pitch and roll moment simulating conditions under which a rotor would be tested in the wind tunnel.

Friedmann, P.↗

Kinetic theory based new upwind methods for inviscid compressible flows

Two new upwind methods called the Kinetic Numerical Method (KNM) and the Kinetic Flux Vector Splitting (KFVS) method for the solution of the Euler equations have been presented. Both of these methods can be regarded as some suitable moments of an upwind scheme for the solution of the Boltzmann equation provided the distribution function is Maxwellian. This moment-method strategy leads to a unification of the Riemann approach and the pseudo-particle approach used earlier in the development of upwind methods for the Euler equations. A very important aspect of the moment-method strategy is that the new upwind methods satisfy the entropy condition because of the Boltzmann H-Theorem and suggest a possible way of extending the Total Variation Diminishing (TVD) principle within the framework of the H-Theorem. The ability of these methods in obtaining accurate wiggle-free solution is demonstrated by applying them to two test problems.

Deshpande, S. M.↗

Three approaches to reliability analysis

It is noted that current reliability analysis tools differ not only in their solution techniques, but also in their approach to model abstraction. The analyst must be satisfied with the constraints that are intrinsic to any combination of solution technique and model abstraction. To get a better idea of the nature of these constraints, three reliability analysis tools (HARP, ASSIST/SURE, and CAME) were used to model portions of the Integrated Airframe/Propulsion Control System architecture. When presented with the example problem, all three tools failed to produce correct results. In all cases, either the tool or the model had to be modified. It is suggested that most of the difficulty is rooted in the large model size and long computational times which are characteristic of Markov model solutions.

Mesh networks↗

National Space Transportation System (NSTS) technology needs

The National Space Transportation System (NSTS) is one of the Nation's most valuable resources, providing manned transportation to and from space in support of payloads and scientific research. The NSTS program is currently faced with the problem of hardware obsolescence, which could result in unacceptable schedule and cost impacts to the flight program. Obsolescence problems occur because certain components are no longer being manufactured or repair turnaround time is excessive. In order to achieve a long-term, reliable transportation system that can support manned access to space through 2010 and beyond, NASA must develop a strategic plan for a phased implementation of enhancements which will satisfy this long-term goal. The NSTS program has initiated the Assured Shuttle Availability (ASA) project with the following objectives: eliminate hardware obsolescence in critical areas, increase reliability and safety of the vehicle, decrease operational costs and turnaround time, and improve operational capability. The strategy for ASA will be to first meet the mandatory needs - keep the Shuttle flying. Non-mandatory changes that will improve operational capability and enhance performance will then be considered if funding is adequate. Upgrade packages should be developed to install within designated inspection periods, grouped in a systematic approach to reduce cost and schedule impacts, and allow the capability to provide a Block 2 Shuttle (Phase 3).

Winterhalter, David L.↗

Hybrid Upwind Splitting (HUS) by a Field-by-Field Decomposition

We introduce and develop a new approach for upwind biasing: the hybrid upwind splitting (HUS) method. This original procedure is based on a suitable hybridization of current prominent flux vector splitting (FVS) and flux difference splitting (FDS) methods. The HUS method is designed to naturally combine the respective strengths of the above methods while excluding their main deficiencies. Specifically, the HUS strategy yields a family of upwind methods that exhibit the robustness of FVS schemes in the capture of nonlinear waves and the accuracy of some FDS schemes in the resolution of linear waves. We give a detailed construction of the HUS methods following a general and systematic procedure directly performed at the basic level of the field by field (i.e. waves) decomposition involved in FDS methods. For such a given decomposition, each field is endowed either with FVS or FDS numerical fluxes, depending on the nonlinear nature of the field under consideration. Such a design principle is made possible thanks to the introduction of a convenient formalism that provides us with a unified framework for upwind methods. The HUS methods we propose bring significant improvements over current methods in terms of accuracy and robustness. They yield entropy-satisfying approximate solutions as they are strongly supported in numerical experiments. Field by field hybrid numerical fluxes also achieve fairly simple and explicit expressions and hence require a computational effort between that of the FVS and FDS. Several numerical experiments ranging from stiff 1D shock-tube to high speed viscous flows problems are displayed, intending to illustrate the benefits of the present approach. We assess in particular the relevance of our HUS schemes to viscous flow calculations.

Coquel, Frederic↗

Heterogeneous Superconducting Low-Noise Sensing Coils

A heterogeneous material construction has been devised for sensing coils of superconducting quantum interference device (SQUID) magnetometers that are subject to a combination of requirements peculiar to some advanced applications, notably including low-field magnetic resonance imaging for medical diagnosis. The requirements in question are the following: The sensing coils must be large enough (in some cases having dimensions of as much as tens of centimeters) to afford adequate sensitivity; The sensing coils must be made electrically superconductive to eliminate Johnson noise (thermally induced noise proportional to electrical resistance); and Although the sensing coils must be cooled to below their superconducting- transition temperatures with sufficient cooling power to overcome moderate ambient radiative heat leakage, they must not be immersed in cryogenic liquid baths. For a given superconducting sensing coil, this combination of requirements can be satisfied by providing a sufficiently thermally conductive link between the coil and a cold source. However, the superconducting coil material is not suitable as such a link because electrically superconductive materials are typically poor thermal conductors. The heterogeneous material construction makes it possible to solve both the electrical- and thermal-conductivity problems. The basic idea is to construct the coil as a skeleton made of a highly thermally conductive material (typically, annealed copper), then coat the skeleton with an electrically superconductive alloy (typically, a lead-tin solder) [see figure]. In operation, the copper skeleton provides the required thermally conductive connection to the cold source, while the electrically superconductive coating material shields against Johnson noise that originates in the copper skeleton.

Hahn, Inseob↗