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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

l1-optimal control of multivariable systems with output norm constraints

This paper considers the l1-optimal control problem for general rational plants. It is shown that, for plants with no poles or zeros on the unit circle, an optimal compensator exists and that the resulting closed loop transfer function is polynomial whenever there are at least as many controls as regulated outputs and at least as many measurements as exogeneous inputs. Exactly or approximately, optimal rational compensators can be obtained by solving a sequence of finite linear programs for the coefficients of a polynomial closed-loop transfer function. No assumptions on plant poles or zeros are required to obtain at least approximately optimal compensators. It is shown that constrained problems in which a set of outputs is regulated subject to l(infinity)-norm constraints on another set of outputs can be solved using a slight modification of the same algorithm.

Mcdonald, J. S.↗
DOE OSTI2025

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗
DOE OSTI2023

Learning to concentrate: multi-tracer forecasts on local primordial non-Gaussianity with machine-learned bias

Local primordial non-Gaussianity (LPNG) is predicted by many non-minimal models of inflation, and creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers, whose amplitude is characterized by b Φ . Knowledge of b Φ for the observed tracer population is therefore crucial for learning about inflation from LSS. Recently, it has been shown that the relationship between linear bias b 1 and b Φ for simulated halos exhibits significant secondary dependence on halo concentration. We leverage this fact to forecast multi-tracer constraints on ${f}^{loc}_{NL}$. We train a machine learning model on observable properties of simulated IllustrisTNG galaxies to predict b Φ for samples constructed to approximate DESI emission line galaxies (ELGs) and luminous red galaxies (LRGs). We find σ(${f}^{loc}_{NL}$) = 2.3, and σ(${f}^{loc}_{NL}$) = 3.7, respectively. These forecasted errors are roughly factors of 3, and 35% improvements over the single-tracer case for each sample, respectively. When considering both ELGs and LRGs in their overlap region, we forecast σ(${f}^{loc}_{NL}$) = 1.5 is attainable with our learned model, more than a factor of 3 improvement over the single-tracer case, while the ideal split by b Φ could reach σ(${f}^{loc}_{NL}$) < 1. In conclusion, we also perform multi-tracer forecasts for upcoming spectroscopic surveys targeting LPNG (MegaMapper, SPHEREx) and show that splitting tracer samples by b Φ can lead to an order-of-magnitude reduction in projected σ(${f}^{loc}_{NL}$) for these surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System

This paper presents a load switching group based energy management system (LSG-EMS) for operating microgrids on a distribution feeder powered by one or multiple grid-forming distributed energy resources. Loads on a distribution feeder are divided into load switching groups that can be remotely switched on and off. The LSG-EMS algorithm, formulated as a mixed-integer linear programming (MILP) problem, has an objective function of maximizing the served loads while minimizing the total number of switching actions. A new set of topology constraints are developed for allowing multiple microgrids to be formed on the feeder and selecting the optimal supply path. Customer comfort is accounted for by maximizing the supply duration in the customer preferred service period and enforcing a minimum service duration. The proposed method is demonstrated on a modified IEEE 33-bus system using actual customer data. Simulation results show that the LSG-EMS successfully coordinates multiple grid-forming sources by selecting an optimal supply topology that maximizes the supply period of both the critical and noncritical loads while minimizing customer service interruptions in the service restoration process.

Hu, Rongxing↗
NASA NTRS1972

Maximum range three-dimensional lifting planetary entry

Variational equations for maximum range three-dimensional quasisteady glide are given. Nonlinear oscillatory maximum range trajectories obtained with a refined gradient program are approximated by a superposition of quasisteady glide and linearized perturbation equation results. A basic control law is found which is closely followed for maximum cross-range trajectories. The effect of a reradiative heating constraint involving velocity, altitude and angle of attack on a maximum cross-range trajectory for a space shuttle orbiter-type vehicle reentering the earth's atmosphere is investigated numerically.

Dickmanns, E. D.↗
NASA NTRS1983

An application of nonlinear programming to the design of regulators of a linear-quadratic formulation

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a nonlinear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer. One concerns helicopter longitudinal dynamics and the other the flight dynamics of an aerodynamically unstable aircraft.

Fleming, P.↗
NASA NTRS1984

Output feedback and generic stabilizability

Attention is given to questions of pole placement and stabilization for generic linear systems with prescribed state, input and output dimension for the case where the controller must be implemented by linear memoryless output feedback. A criterion is presented in terms of a special pole placement property for generic stabilizability, and this criterion is used to describe constraints on the dimension which are consistent with generic stabilizability. Also treated are the rationality and solvability by radicals of stabilizing or pole positioning gains, and the way in which decision algebra can theoretically handle existence questions for generic systems is described.

Byrnes, C. I.↗
NASA NTRS1987

The significance of error dynamics in model-following for flight control design

The role of the system error dynamics in model-following control systems is discussed, along with the use of handling quality specifications, actuation bandwidth constraints, stability, and closed-loop performance requirements in flight control design. The model-following problem is formulated using both direct state-space and linear, quadratic, optimization techniques. The results are then demonstrated using several examples involving a generic forward-swept-wing vehicle and a conventional flight vehicle with large parameter uncertainty in order to illustrate the trade-off in closed-loop performance and control law complexity.

Schmidt, David K.↗
NASA NTRS1988

An efficient multilevel optimization method for engineering design

An efficient multilevel deisgn optimization technique is presented. The proposed method is based on the concept of providing linearized information between the system level and subsystem level optimization tasks. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to use. The disadvantage is that the coupling between subsystems is not dealt with in a precise mathematical manner.

Vanderplaats, G. N.↗
NASA NTRS1992

Retrieval of a wind profile from the Galileo Probe telemetry signal

The zonal wind speed profile within Jupiter's upper troposphere is to be estimated on the basis of its influence on the frequency of the Galileo Probe's telemetry signal; this is achieved by linearizing the relativistic Doppler shift equation about a state of zero wind speed, expanding the zonal wind series in a Legendre polynomial series, and reducing the resulting equations to a linear, least-squares problem. If the error sources have magnitudes not greater than those presently assumed, the retrieved wind speed profiles can place a key constraint on the basic drive for the atmospheric circulation, as well as anchoring winds derived from Galileo Orbiter images to well-defined vertical positions in the atmosphere.

Pollack, James B.↗
NASA NTRS1996

Application of Optimization Techniques to Design of Unconventional Rocket Nozzle Configurations

Several current rocket engine concepts such as the bell-annular tri-propellant engine, and the linear aerospike being proposed for the X-33 require unconventional three dimensional rocket nozzles which must conform to rectangular or sector shaped envelopes to meet integration constraints. These types of nozzles exist outside the current experience database, therefore, the application of efficient design methods for these propulsion concepts is critical to the success of launch vehicle programs. The objective of this work is to optimize several different nozzle configurations, including two- and three-dimensional geometries. Methodology includes coupling computational fluid dynamic (CFD) analysis to genetic algorithms and Taguchi methods as well as implementation of a streamline tracing technique. Results of applications are shown for several geometeries including: three dimensional thruster nozzles with round or super elliptic throats and rectangualar exits, two- and three-dimensional thrusters installed within a bell nozzle, and three dimensional thrusters with round throats and sector shaped exits. Due to the novel designs considered for this study, there is little experience which can be used to guide the effort and limit the design space. With a nearly infinite parameter space to explore, simple parametric design studies cannot possibly search the entire design space within the time frame required to impact the design cycle. For this reason, robust and efficient optimization methods are required to explore and exploit the design space to achieve high performance engine designs. Five case studies which examine the application of various techniques in the engineering environment are presented in this paper.

Follett, W.↗
NASA NTRS1994

An Algorithm to Generate Deep-Layer Temperatures from Microwave Satellite Observations for the Purpose of Monitoring Climate Change

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate. The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: (1) the sum of the coefficients must be one, (2) the noise of the product is minimized, and (3) the shape of the approximated averaging kernel is well-behaved. Note that a trade-off between constraints 2 and 3 is unavoidable. The algorithm can also be used to combine measurements from a future sensor (i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)) to yield the same averaging kernel as that based on an earlier sensor (i.e., the 4-channel Microwave Sounding Unit (MSU)). This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

Goldberg, Mitchell D.↗
NASA NTRS2018

Görtler Instability and Its Control via Surface Suction over an Axisymmetric Cone at Mach 6

The characteristics of Görtler instability over an axisymmetric cone with an aft concave section are studied via linear and nonlinear instability analysis and direct numerical simulations. Several options for the cone geometry have been investigated numerically, subject to a fixed forecone section and constraints on the maximum cone diameter, overall cone length, and minimum N-factor for the most amplified Görtler modes. Computations show that it is possible to design a cone with a peak N-factor of Nmax > 8 at the target Reynolds number of 12.1×10(exp 6) per meter, corresponding to the maximum quiet Reynolds number in the Boeing/AFOSR Mach-6 Quiet Tunnel at Purdue University. Direct numerical simulations show that an array of roughness elements corresponding to a peak roughness height of 0.1006 mm at the center can excite Görtler vortices that evolve into sufficiently strong streamwise streaks that may break down via high-frequency secondary instability. Thus, the selected axisymmetric configuration of interest should provide an acceptable baseline to investigate the feasibility of several aspects of laminar-flow control via boundary-layer suction. The apparatus that is being used for measurements in the Boeing/AFOSR Quiet Tunnel is described, along with some preliminary experimental results.

Gortler vortices↗
DOE OSTI2022

Enabling Grid-Aware Market Participation of Aggregate Flexible Resources

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With the new FERC 2222 order, DER aggregations are allowed to participate in energy market. To enable market participation, these virtual power plants need to provide their generation cost curves. This paper proposes efficient optimization formulations and solution approaches for the characterization of hourly as well as multi-time-step generation cost curves for a distribution system with high penetration of DERs. Network and DER constraints are taken into account when deriving these cost curves, and they enable active distribution systems to bid into the electricity market. The problems of deriving linear and quadratic cost curves are formulated as robust optimization problems and tractable reformulation/solution algorithm are developed to facilitate efficient calculations. The proposed formulations and solution algorithm are validated on a realistic test feeder with high penetration of flexible resources.

aggregated distributed energy resources↗
DOE OSTI2020

Evidence and modeling of turbulence bifurcation in L-mode confinement transitions on Alcator C-Mod

Analysis and modeling of rotation reversal hysteresis experiments show that a single turbulent bifurcation is responsible for the Linear to Saturated Ohmic Confinement (LOC/SOC) transition and concomitant intrinsic rotation reversal on Alcator C-Mod. Plasmas on either side of the reversal exhibit different toroidal rotation profiles and therefore different turbulence characteristics despite the profiles of density and temperature, which are indistinguishable within measurement uncertainty. Elements of this bifurcation are also shown to persist for auxiliary heated L-modes. The deactivation of subdominant (in the linear growth rate and contribution to heat transport) ion temperature gradient and trapped electron mode instabilities is identified as the only possible change in turbulence within a reduced quasilinear transport model across the reversal, which is consistent with the measured profiles and inferred heat and particle fluxes. Experimental constraints on a possible change from strong to weak turbulence, outside the description of the quasilinear model, are also discussed. These results indicate an explanation for the LOC/SOC transition that provides a mechanism for the hysteresis through the dynamics of subdominant modes and changes in their relative populations and does not involve a change in the most linearly unstable ion-scale drift-wave instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Resilient Operating Constraints for Power Distribution Systems under Setpoint Attacks

Integration and operation of distributed generation (DG) and energy storage (ES) in power distribution systems are enabled by communication networks and embedded sensor and control devices that increase the vulnerability of the systems to cyber-threats, broadening the attack surface and making adversary actions more unpredictable. This paper proposes a methodology that uses ellipsoidal approximations to quantify the potential damage caused by successful attacks that affect, directly or indirectly, the desired operation setpoints and may drive the power distribution operation to unsafe states by violating the limits of voltage or line flows. More specifically, a new methodology is introduced to find the optimal non-symmetric operating constraints that can be imposed to each DG and ES in order to guarantee that the power distribution system is resilient to any malicious setpoints. The proposed method takes as inputs the system topology, DG and ES capabilities, and load limits to solve a convex optimization problem formulated using linear matrix inequalities (LMIs) and the power flow equations. The proposed solution is agnostic to the attacker's action or load profile and it does not require any assumption about the location or means of the attack. The numerical results on a test distribution feeder with several DG and ES illustrate how the proposed resilient operating constraints guarantee the security of the power distribution system under setpoint attacks.

Giraldo, Jairo↗
DOE OSTI2025

Determination of Constraint-Independent Crack Tip Opening Angle for Stable Crack Growth in High-Strength Ductile Steels

The crack tip opening angle (CTOA) is one of fracture toughness parameters that has been used for decades in describing large stable crack growth in thin-walled aerospace structures under the low-constraint conditions. Recently, the pipeline industry has developed a growing interest in using the CTOA parameter to serve as the minimum required fracture toughness to arrest dynamic crack propagation in modern gas transmission pipelines made of high-strength ductile steel. To meet this industrial need, the CTOA test standard ASTM E3039 was therefore developed for measuring the constant critical CTOA. ASTM E3039 recommends a drop weight tearing test (DWTT) specimen with a shallow crack for standard CTOA testing, but its CTOA may depend on the low constraint condition of the DWTT specimen at the crack tip. Verifying the constraint independence of the DWTT-measured CTOA thus becomes indispensable for applying CTOA toughness to the running fracture control in the pipeline design. For this purpose, the present paper evaluates critical CTOA values in a set of fracture toughness tests on single-edge notched bend (SENB) specimens with shallow and deep cracks, based on four CTOA estimation models. Among these, the Ln(P)-LLD linear fit model is similar to that recommended by ASTM E3039 for CTOA calculation. Fracture test data for X80 pipeline steel and HY80 structural steel were considered in the CTOA evaluation. The results showed that the four CTOA models were able to determine a constraint independent CTOA value for stable crack growth in the SENB specimens. As a result, a single, reliable, constant CTOA value could be determined regardless of the specimen geometry or the crack-tip constraint conditions. Therefore, the CTOA measured using ASTM E3039 is constraint-independent and transferable to use in cases of actual cracks propagating in gas transmission pipelines.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamic Modeling, Trajectory Optimization, and Linear Control of Cable-Driven Parallel Robots for Automated Panelized Building Retrofits

The construction industry faces a growing need for automation to reduce costs, improve accuracy and productivity, and address labor shortages. One area that stands to benefit significantly from automation is panelized prefabricated building envelope retrofits, which can improve a building’s energy efficiency in heating and cooling interior spaces. In this paper, we propose using cable-driven parallel robots (CDPRs), which can effectively lift and handle large objects, to install these panels. However, implementing CDPRs presents significant challenges because of their nonlinear dynamics, complex trajectory planning, and precise control requirements. To tackle these challenges, this work focuses on a new application of established control and trajectory optimization theories in a CDPR simulation of a building envelope retrofit under real-world conditions. We first model the dynamics of CDPRs, highlighting the critical role of damping in system behavior. Building on this dynamic model, we formulate a trajectory optimization problem to generate feasible and efficient motion plans for the robot under operational and environmental constraints. Given the high precision required in the construction industry, accurately tracking the optimized trajectory is essential. However, challenges such as partial observability and external vibrations complicate this task. To address these issues, a Linear Quadratic Gaussian control framework is applied, enabling the robot to track the optimized trajectories with precision. Simulation results show that the proposed controller enables precise end effector positioning with errors under 4 mm, even in the presence of external wind disturbances. Through comprehensive simulations, our approach allows for an in-depth exploration of the system’s nonlinear dynamics, trajectory optimization, and control strategies under controlled yet highly realistic conditions. The results demonstrate the feasibility of CDPRs for automating panel installation and provide insights into their practical deployment.

CDPR↗