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DOE OSTI2023

Impact of High Energy νe (ν¯e) Events on NOvA Oscillation Sensitivities

NOvA is a two detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is primarily designed to constraint neutrino oscillation parameters using muon neutrino (anti-neutrino) disappearance data and electron neutrino (anti-neutrino) appearance data. NOvA detects neutrinos from Fermilab’s Neutrinos at Main Injector (NuMI) beam-line. The un-oscillated muon neutrino and beam $\nu_e$ events are observed by the NOvA Near Detector (ND), which is 100m underground and at a distance of 1km from the beam source. The Far Detector (FD), situated 809 km away from the ND, is in Ash River, MN, USA, and observes $\nu_\mu$ and $\nu_e$ events after oscillations. Traditionally, NOvA has used $\nu_e$ events in the energy range 1 < E < 4 GeV for 3-flavor neutrino oscillation analyses to constraint the neutrino oscillation parameters. In this study we looked at the impact of including high-energy neutrino events with energies up to 12 GeV in the analysis with the aim of constraining the beam electron neutrino/antineutrino background events. Event count predictions after adding this high-energy sample events and latest three flavor oscillation results of the NOvA experiment are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1982

Some interdisciplinary trade-offs in the design of large space structures

The constraints placed on the design of large space structures by acceleration, attitude control, and stationkeeping forces are discussed. Stiffness requirements for the structures are derived. The use of active versus passive accuracy control methods is also addressed.

Hedgepeth, J. M.↗

NASA NTRS2021

Mission Concept Design for Autonomous Space Missions using Mission-Level Modeling and Simulation

NASA’s Europa Lander mission is to search for biosignatures on Europa based on in-situ science using a lander architecture. This mission presents a set of challenges that requires a high level of autonomy on the lander system, leading to the need for a new operational paradigm that supports better collaboration and coordination between the lander and the ground operations team. M\&S is used for both designing the onboard system-level autonomy and the ground operations paradigm that allows effective and efficient collaboration and coordination between the lander and the ground operations team. In this paper, M\&S as applied to the design of new mission and operational concepts will be discussed. At its current early stage of the mission development for Europa Lander, the M\&S is used to explore different mission concepts and gain insights for design (formative) rather than to verify and validate fully designed mission concepts quantitatively (summative). Organically, we established a new approach to mission and operational concept exploration using high-fidelity modeling and simulation. M\&S has been an integral part of the approach of defining constraints and assertions, designing mission concepts, assessing (i.e., simulating them), and discovering insights, which feeds back to the definition an design steps. This organically-established approach provided important benefits to the project at its early phase of the development by enabling the project team to be able to build shared understanding of impacts from design characteristics, constraints, and their interactions on the mission performance.

Ye, Sean↗

NASA NTRS1990

Direct handling of equality constraints in multilevel optimization

In recent years there have been several hierarchic multilevel optimization algorithms proposed and implemented in design studies. Equality constraints are often imposed between levels in these multilevel optimizations to maintain system and subsystem variable continuity. Equality constraints of this nature will be referred to as coupling equality constraints. In many implementation studies these coupling equality constraints have been handled indirectly. This indirect handling has been accomplished using the coupling equality constraints' explicit functional relations to eliminate design variables (generally at the subsystem level), with the resulting optimization taking place in a reduced design space. In one multilevel optimization study where the coupling equality constraints were handled directly, the researchers encountered numerical difficulties which prevented their multilevel optimization from reaching the same minimum found in conventional single level solutions. The researchers did not explain the exact nature of the numerical difficulties other than to associate them with the direct handling of the coupling equality constraints. The coupling equality constraints are handled directly, by employing the Generalized Reduced Gradient (GRG) method as the optimizer within a multilevel linear decomposition scheme based on the Sobieski hierarchic algorithm. Two engineering design examples are solved using this approach. The results show that the direct handling of coupling equality constraints in a multilevel optimization does not introduce any problems when the GRG method is employed as the internal optimizer. The optimums achieved are comparable to those achieved in single level solutions and in multilevel studies where the equality constraints have been handled indirectly.

Renaud, John E.↗

NASA NTRS1984

Optimization of Antenna Structure Design

Optimality criteria design is applied for large antenna structures with multiple constraints on microwave performance. The constraints are on accuracy of the structure: restrictions on the microwave pathlength error, and the antenna pointing error. The examples given show convergence to low-weight feasible designs that satisfy the constraints. Truss-member sizes are automatically selected from tables of commercially available structural shapes, and approximations results from the method of selection are found moderate. The multiple constraint design is shown to be more effective in meeting constraints than the old envelop method. For practical structures, the new design method can be performed within reasonable core size and computation time.

Levy, R.↗

NASA NTRS1989

General approach and scope

This paper describes a joint activity involving NASA and Army researchers at the NASA Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure will be closely coupled, while acoustics and airframe dynamics will be decoupled and be accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is to be integrated with the first three disciplines. Finally, in phase 3, airframe dynamics will be fully integrated with the other four disciplines. This paper deals with details of the phase 1 approach and includes details of the optimization formulation, design variables, constraints, and objective function, as well as details of discipline interactions, analysis methods, and methods for validating the procedure.

Adelman, Howard M.↗

DOE OSTI2022

Transformational Challenge Reactor – On the Application of Design for Additive Manufacturing (DfAM) Techniques to the Conception of Nuclear Core

Additive manufacturing (AM) technologies are radically changing the way objects are designed and manufactured. They allow building by deposition and solidification of material layer by layer, enabling the possibility to create simple and complex features alike, almost seamlessly. Generally, the design optimization process requires to define objectives, design variables and constraints. Additive manufacturing does not challenge this process per se but does allow designers to completely redefine the constraints space as the ones originating from fabrication can be considerably relaxed compared to more “traditional” manufacturing. Thus, design optimization becomes naturally far more responsive to the actual physics being solved and considerably less influenced by fabrication limitations, leading to dramatically different designs. To take advantage of these new opportunities, so-called Designing for Additive Manufacturing (DfAM) techniques are emerging. Development of design techniques specifically tailored for additive manufacturing is warranted because, considering AM, the design space is typically considerably larger than with traditional manufacturing. The ability to explore the design space efficiently is of paramount importance for designers. This study proposes to investigate and apply some of these DfAM techniques to the conception of nuclear core. The goal being to assess if these new methods can be applied to core design and if core design could benefits from additive manufacturing technologies. After a brief investigation on the pertinence of some DfAM techniques for core design, algorithms are proposed and a workflow is established to carry neutronics and steady-state thermal-hydraulics analyses. To diminish the work load, the workflow has been automated using python modules. These modules allow the rapid creation of input files, post-treatment of output files and visualization. To test the pertinence of the proposed workflow, three test cases have been investigated: a research and test reactor, a micro-reactor and a space propulsion reactor. These test cases offered a variety of objectives, constraints and operating conditions. It is observed that the proposed workflow is capable of converging quickly and efficiently to valid design solutions. It is then concluded that DfAM techniques can be applied to core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2011

Formal Verification Toolkit for Requirements and Early Design Stages

Efficient flight software development from natural language requirements needs an effective way to test designs earlier in the software design cycle. A method to automatically derive logical safety constraints and the design state space from natural language requirements is described. The constraints can then be checked using a logical consistency checker and also be used in a symbolic model checker to verify the early design of the system. This method was used to verify a hybrid control design for the suit ports on NASA Johnson Space Center's Space Exploration Vehicle against safety requirements.

Badger, Julia M.↗

NASA NTRS1989

Optimization by decomposition: A step from hierarchic to non-hierarchic systems

A new, non-hierarchic decomposition is formulated for system optimization that uses system analysis, system sensitivity analysis, temporary decoupled optimizations performed in the design subspaces corresponding to the disciplines and subsystems, and a coordination optimization concerned with the redistribution of responsibility for the constraint satisfaction and design trades among the disciplines and subsystems, and a coordination optimization concerned with the redistribution of responsibility for the constraint satisfaction and design trades among the disciplines and subsystems. The approach amounts to a variation of the well-known method of subspace optimization modified so that the analysis of the entire system is eliminated from the subspace optimization and the subspace optimizations may be performed concurrently.

Sobieszczanski-Sobieski, Jaroslaw↗

NASA NTRS1989

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented.

Lucas, S. H.↗

NASA NTRS2017

NASA's Advanced Exploration Systems Mars Transit Habitat Refinement Point of Departure Design

This paper describes the recently developed point of departure design for a long duration, reusable Mars Transit Habitat, which was established during a 2016 NASA habitat design refinement activity supporting the definition of NASA's Evolvable Mars Campaign. As part of its development of sustainable human Mars mission concepts achievable in the 2030s, the Evolvable Mars Campaign has identified desired durations and mass/dimensional limits for long duration Mars habitat designs to enable the currently assumed solar electric and chemical transportation architectures. The Advanced Exploration Systems Mars Transit Habitat Refinement Activity brought together habitat subsystem design expertise from across NASA to develop an increased fidelity, consensus design for a transit habitat within these constraints. The resulting design and data (including a mass equipment list) contained in this paper are intended to help teams across the agency and potential commercial, academic, or international partners understand: 1) the current architecture/habitat guidelines and assumptions, 2) performance targets of such a habitat (particularly in mass, volume, and power), 3) the driving technology/capability developments and architectural solutions which are necessary for achieving these targets, and 4) mass reduction opportunities and research/design needs to inform the development of future research and proposals. Data presented includes: an overview of the habitat refinement activity including motivation and process when informative; full documentation of the baseline design guidelines and assumptions; detailed mass and volume breakdowns; a moderately detailed concept of operations; a preliminary interior layout design with rationale; a list of the required capabilities necessary to enable the desired mass; and identification of any worthwhile trades/analyses which could inform future habitat design efforts. As a whole, the data in the paper show that a transit habitat meeting the 43 metric tons launch mass/trans-Mars injection burn limits specified by the Evolvable Mars Campaign is achievable near the desired timeframe with moderate strategic investments including maintainable life support systems, repurposable structures and packaging, and lightweight exercise modalities. It also identifies operational and technological options to reduce this mass to less than 41 metric tons including staging of launch structure/packaging and alternate structural materials.

Simon, Matthew↗

NASA NTRS1996

Optimization of Air-Breathing Engine Concept

The design optimization of air-breathing propulsion engine concepts has been accomplished by soft-coupling the NASA Engine Performance Program (NEPP) analyzer with the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Engine problems, with their associated design variables and constraints, were cast as nonlinear optimization problems with thrust as the merit function. Because of the large number of mission points in the flight envelope, the diversity of constraint types, and the overall distortion of the design space; the most reliable optimization algorithm available in COMETBOARDS, when used by itself, could not produce satisfactory, feasible, optimum solutions. However, COMETBOARDS' unique features-which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications-successfully optimized the performance of subsonic and supersonic engine concepts. Even when started from different design points, the combined COMETBOARDS and NEPP results converged to the same global optimum solution. This reliable and robust design tool eliminates manual intervention in the design of air-breathing propulsion engines and eases the cycle analysis procedures. It is also much easier to use than other codes, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capabilities of the combined design tool through the optimization of a high-bypass- turbofan wave-rotor-topped subsonic engine and a mixed-flow-turbofan supersonic engine.

Patnaik, Surya N.↗

NASA NTRS1972

Design of communication systems using short-constraint-length convolutional codes.

A method is presented for calculating the effect of carrier-phase reference error in a receiver phase-locked loop on bit error rates in convolutionally coded data, for the practical design of systems using short-constraint-length convolutional codes. A set of design curves shows the relation between design bit error rate, uplink carrier tracking loop SNR, downlink total SNR, and downlink modulation index. These curves make possible rapid and simple system optimization.

Merrill, H. M.↗

NASA NTRS1988

Minimum weight design of rotorcraft blades with multiple frequency and stress constraints

A method is developed for the minimum weight design of helicopter rotor blades having multiple coupled flap-lag natural frequency constraints, in addition to a constraint on the minimum blade autorotation value that will ensure sufficient rotary inertia for autorotation in the event of engine failure. Design variables encompass blade taper ratio, box beam dimensions, and the magnitudes of the nonstructural weights. Optimum designs have been obtained for both rectangular and tapered blades; attention is given to the optimum blade weight effect and the blade mass and stiffness distribution effects of adding constraints on higher frequencies and stresses.

Chattopadhyay, Aditi↗

NASA NTRS1992

Resource constrained design of artificial neural networks using comparator neural network

We present a systematic design method executed under resource constraints for automating the design of artificial neural networks using the back error propagation algorithm. Our system aims at finding the best possible configuration for solving the given application with proper tradeoff between the training time and the network complexity. The design of such a system is hampered by three related problems. First, there are infinitely many possible network configurations, each may take an exceedingly long time to train; hence, it is impossible to enumerate and train all of them to completion within fixed time, space, and resource constraints. Second, expert knowledge on predicting good network configurations is heuristic in nature and is application dependent, rendering it difficult to characterize fully in the design process. A learning procedure that refines this knowledge based on examples on training neural networks for various applications is, therefore, essential. Third, the objective of the network to be designed is ill-defined, as it is based on a subjective tradeoff between the training time and the network cost. A design process that proposes alternate configurations under different cost-performance tradeoff is important. We have developed a Design System which schedules the available time, divided into quanta, for testing alternative network configurations. Its goal is to select/generate and test alternative network configurations in each quantum, and find the best network when time is expended. Since time is limited, a dynamic schedule that determines the network configuration to be tested in each quantum is developed. The schedule is based on relative comparison of predicted training times of alternative network configurations using comparator network paradigm. The comparator network has been trained to compare training times for a large variety of traces of TSSE-versus-time collected during back-propagation learning of various applications.

Wah, Benjamin W.↗

NASA NTRS1987

Digital robust active control law synthesis for large order systems using constrained optimization

This paper presents a direct digital control law synthesis procedure for a large order, sampled data, linear feedback system using constrained optimization techniques to meet multiple design requirements. A linear quadratic Gaussian type cost function is minimized while satisfying a set of constraints on the design loads and responses. General expressions for gradients of the cost function and constraints, with respect to the digital control law design variables are derived analytically and computed by solving a set of discrete Liapunov equations. The designer can choose the structure of the control law and the design variables, hence a stable classical control law as well as an estimator-based full or reduced order control law can be used as an initial starting point. Selected design responses can be treated as constraints instead of lumping them into the cost function. This feature can be used to modify a control law, to meet individual root mean square response limitations as well as minimum single value restrictions. Low order, robust digital control laws were synthesized for gust load alleviation of a flexible remotely piloted drone aircraft.

Mukhopadhyay, Vivek↗

NASA NTRS1992

Maximum life spiral bevel reduction design

Savage, M.↗

NASA NTRS1992

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed back-cone distance of the spiral bevel gear set for a specified speed ratio, shaft angle, input torque, and power. Significant parameters in the design are: the spiral angle, the pressure angle, the numbers of teeth on the pinion and gear, and the location and size of the four support bearings. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for gradient optimization. After finding the continuous optimum, a designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗