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SAMSAN provides control-system analyst with self-consistent computer algorithms that support large-order control-system design and evaluation studies. Emphasizes sampled-system analysis. SAMSAN reduces burden on analyst by providing set of algorithms well tested and documented and readily integrated for solving control-system problems.
Nonlinear mathematical-programming-based design optimization can be an elegant method. However, the calculations required to generate the merit function, constraints, and their gradients, which are frequently required, can make the process computational intensive. The computational burden can be greatly reduced by using approximating analyzers derived from an original analyzer utilizing neural networks and linear regression methods. The experience gained from using both of these approximation methods in the design optimization of a high speed civil transport aircraft is the subject of this paper. The Langley Research Center's Flight Optimization System was selected for the aircraft analysis. This software was exercised to generate a set of training data with which a neural network and a regression method were trained, thereby producing the two approximating analyzers. The derived analyzers were coupled to the Lewis Research Center's CometBoards test bed to provide the optimization capability. With the combined software, both approximation methods were examined for use in aircraft design optimization, and both performed satisfactorily. The CPU time for solution of the problem, which had been measured in hours, was reduced to minutes with the neural network approximation and to seconds with the regression method. Instability encountered in the aircraft analysis software at certain design points was also eliminated. On the other hand, there were costs and difficulties associated with training the approximating analyzers. The CPU time required to generate the input-output pairs and to train the approximating analyzers was seven times that required for solution of the problem.
A substructure synthesis procedure applicable to structural systems containing general nonconservative terms is presented. In their final form, the non-self-adjoint substructure equations of motion are cast in state vector form through the use of a variational principle. A reduced-order model for each substructure is implemented by representing the substructure as a combination of a small number of Ritz vectors. For the method presented, the substructure Ritz vectors are identified as a truncated set of substructure eigenmodes, which are typically complex, along with a set of generalized real attachment modes. The formation of the generalized attachment modes does not require any knowledge of the substructure flexible modes; hence, only the eigenmodes used explicitly as Ritz vectors need to be extracted from the substructure eigenproblem. An example problem is presented to illustrate the method.
A substructure synthesis procedure applicable to structural systems containing general nonconservative terms is presented. In their final form, the nonself-adjoint substructure equations of motion are cast in state vector form through the use of a variational principle. A reduced-order mode for each substructure is implemented by representing the substructure as a combination of a small number of Ritz vectors. For the method presented, the substructure Ritz vectors are identified as a truncated set of substructure eigenmodes, which are typically complex, along with a set of generalized real attachment modes. The formation of the generalized attachment modes does not require any knowledge of the substructure flexible modes; hence, only the eigenmodes used explicitly as Ritz vectors need to be extracted from the substructure eigenproblem. An example problem is presented to illustrate the method.
NASA and the U.S. Air Force are working on a joint project to develop a new hydrogen-fueled, full-flow, staged combustion rocket engine. The initial testing and modeling work for the Integrated Powerhead Demonstrator (IPD) project is being performed by NASA Marshall and Stennis Space Centers. A key factor in the testing of this engine is the ability to predict and measure the transient fluid flow during engine start and shutdown phases of operation. A model built by NASA Marshall in the ROCket Engine Transient Simulation (ROCETS) program is used to predict transient engine fluid flows. The model is initially calibrated to data from previous tests on the Stennis E1 test stand. The model is then used to predict the next run. Data from this run can then be used to recalibrate the model providing a tool to guide the test program in incremental steps to reduce the risk to the prototype engine. In this paper, they define this type of model as a calibrated model. This paper proposes a method to estimate the uncertainty of a model calibrated to a set of experimental test data. The method is similar to that used in the calibration of experiment instrumentation. For the IPD example used in this paper, the model uncertainty is determined for both LOX and LH flow rates using previous data. The successful use of this model is then demonstrated to predict another similar test run within the uncertainty bounds. The paper summarizes the uncertainty methodology when a model is continually recalibrated with new test data. The methodology is general and can be applied to other calibrated models.
A variable noise reduction system consists of equipment on board an airplane that is designed to reduce noise in the vicinity of airports. They are anticipated to be used on supersonic civil aircraft currently under development by industry. They are investigated in this paper for a notional 55-tonne supersonic business jet. The airplane concept was developed by NASA for use in environmental impact studies conducted by the International Civil Aviation Organization. The variable noise reduction system investigated implements a programmed thrust lapse procedure and a programmed flap retraction procedure. The procedures are expected to reduce noise in aircraft certification as well as in operational practice. Behavior of the aircraft in a noise certification setting is considered. Variables of the procedures are optimized to reduce noise levels. Certification considerations unique to these systems are discussed for transport-category large airplanes and for jet-powered airplanes. A novel method for evaluating lateral noise is used.
Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.
A number of rotary wing flight tests have been conducted by the Army Aeroflightdynamics Directorate in cooperation with NASA which involved the use of night vision devices and simulated devices. The test set up and data analysis have been taken from two perspectives. Some of the flight tests were structured to look at aircraft handling qualities when the pilot's image quality was reduced from normal daylight levels. In this case, aircraft flight path information was given to the pilot as one input into the Handling Qualities Ratings. Other flight tests were structured to look at pilot and workload directly. In this second case, aircraft position was accurately measured and used as pilot performance data. This paper provides an overview of the test methods used, lessons learned, and recommendations for future tam of night vision devices.
We propose methods that efficiently impose integrality — i.e., the condition that the coefficients of characters in the partition function must be integers — into numerical modular bootstrap. We demonstrate the method with a number of examples where it can be used to strengthen modular bootstrap results. First, we show that, with a mild extra assumption, imposing integrality improves the bound on the maximal allowed gap in dimensions of operators in theories with a U(1) c symmetry at c = 3, and reduces it to the value saturated by the SU(4) 1 WZW model point of c = 3 Narain lattices moduli space. Second, we show that our method can be used to eliminate all but a discrete set of points saturating the bound from previous Virasoro modular bootstrap results. Finally, when central charge is close to 1, we can slightly improve the upper bound on the scaling dimension gap.
The paper presents asymptotic methods for high-aspect-ratio wings in transonic flow developed for straight unyawed wings and for oblique wings. They show that the three-dimensional mixed-flow calculations may be reduced to solving a set of two-dimensional problems at each span station; the development of this theory and the related computational studies are reviewed. Differences between the piloted (oblique) wing, the swept-back wing, and the swept-forward-wing in the induced upwash are discussed; examples of similarity solutions are demonstrated for high subcritical and slightly supercritical component flows, and comparisons made with relaxation solutions of a full potential equation. The examples include oblique and symmetric swept wings, and the adequacy of the existing full-potential computer code is examined.
A method is presented for achieving a dramatic improvement in phase tracking of square wave subcarriers or other square waves. The method is to set the amplitude of the phase quadrature reference signal to zero except near the zero crossings of the input signal. Without changing the loop bandwidth, the variance of the phase error can be reduced to approximately W sigma(sub 0)(2), were sigma (sub 0)(2) is the phase error variance without windowing, and W is the fraction of cycle in which the reference signal has a nonzero value. Simulation results confirm the analysis and establish minimum W versus signal-to-noise ratio. Typically, the window can be made so narrow as to achieve a phase error variance of 1.5 sigma(sub 0)(4).
A method is presented for achieving a dramatic improvement in phase tracking of square wave subcarriers or other square waves. The method is to set the amplitude of the phase quadrature reference signal to zero except near the zero crossings of the input signal. Without changing the loop bandwidth, the variance of the phase error can be reduced to approximately W sigma(sub 0)(2), where sigma (sub 0)(2) is the phase error variance without windowing, and W is the fraction of cycle in which the reference signal has a nonzero value. Simulation results confirm the analysis and establish minimum W versus signal-to-noise ratio. Typically, the window can be made so narrow as to achieve a phase error variance of 1.5 sigma(sub 0)(4).
The geometric structure of Cr(CO)6 is optimized at the modified coupled-pair functional (MCPF), single and double excitation coupled-cluster (CCSD) and CCSD(T) levels of theory (including a perturbational estimate for connected triple excitations), and the force constants for the totally symmetric representation are determined. The geometry of Cr(CO)5 is partially optimized at the MCPF, CCSD and CCSD(T) levels of theory. Comparison with experimental data shows that the CCSD(T) method gives the best results for the structures and force constants, and that remaining errors are probably due to deficiencies in the one-particle basis sets used for CO. A detailed comparison of the properties of free CO is therefore given, at both the MCPF and CCSD/CCSD(T) levels of treatment, using a variety of basis sets. With very large one-particle basis sets, the SSCD(T) method gives excellent results for the bond distance, dipole moment and harmonic frequency of free CO. The total binding energies of Cr(CO)6 and Cr(CO)5 are also determined at the MCPF, CCSD and CCSD(T) levels of theory. The CCSD(T) method gives a much larger total binding energy than either the MCPF or CCSD methods. An analysis of the basis set superposition error (BSSE) at the MCPF level of treatment points out limitations in the one-particle basis used here and in a previous study. Calculations using larger basis sets reduced the BSSE, but the total binding energy of Cr(CO)6 is still significantly smaller than the experimental value, although the first CO bond dissociation energy of Cr(CO)6 is well described. An investigation of 3s3p correlation reveals only a small effect. The remaining discrepancy between the experimental and theoretical total binding energy of Cr(CO)6 is probably due to limitations in the one-particle basis, rather than limitations in the correlation treatment. In particular an additional d function and an f function on each C and O are needed to obtain quantitative results. This is underscored by the fact that even using a very large primitive se (1042 primitive functions contracted to 300 basis functions), the superposition error for the total binding energy of Cr(CO)6 is 22 kcal/mol at the MCPF level of treatment.
This paper outlines a method for reducing astrometric data to derive the closest approach time and distance to the center of an occultation shadow for a single observer. The method applies to CCD frames, strip scans or photographic plates and uses a set of field stars of unknown positions to define a common coordinate system for all frames. The motion of the occulting body is used to establish the transformation between this common coordinate system and the celestial coordinate system of the body's ephemeris. This method is demonstrated by application to the Tr6O occultation by Triton on 1993 July 10 UT. Over an interval of four nights that included the occultation time, 80 frames of Triton and Tr6O were taken near the meridian with the U.S. Naval Observatory (USNO) 61-inch astrometric reflector. Application of the method presented here to these data yields a closest approach distance of 359 +/- 133 km (corresponding to 0.017 +/- 0.006 arcsec) for the occultation chord obtained with the Kuiper Airborne Observatory (KAO). Comparison of the astrometric closest approach time with the KAO light-curve midtime shows a difference of 2.2 +/- 4.1 s. Relative photometry of Triton and Tr6O, needed for photometric calibration of the occultation light curve, is also presented.
A premixed, shock-induced combustion engine has been proposed in the past as a viable option for operating in the Mach 10 to 15 range in a single stage to orbit vehicle. In this approach, a shock is used to initiate combustion in a premixed fuel/air mixture. Apparent advantages over a conventional scramjet engine include a shorter combustor that, in turn, results in reduced weight and heating loads. There are a number of technical challenges that must be understood and resolved for a practical system: premixing of fuel and air upstream of the combustor without premature combustion, understanding and control of instabilities of the shock-induced combustion front, ability to produce sufficient thrust, and the ability to operate over a range of Mach numbers. This study evaluated the stability of the shock-induced combustion front in a model problem of a sphere traveling in a fuel/air mixture at high Mach numbers. A new, rapid analysis method was developed and applied to study such flows. In this method the axisymmetric, body-centric Navier-Stokes equations were expanded about the stagnation streamline of a sphere using the local similarity hypothesis in order to reduce the axisymmetric equations to a quasi-1D set of equations. These reduced sets of equations were solved in the stagnation region for a number of flow conditions in a premixed, hydrogen/air mixture. Predictions from the quasi-1D analysis showed very similar stable or unstable behavior of the shock-induced combustion front as compared to experimental studies and higher-fidelity computational results. This rapid analysis tool could be used in parametric studies to investigate effects of fuel rich/lean mixtures, non-uniformity in mixing, contaminants in the mixture, and different chemistry models.
DSMC Analysis Code (DAC) is a flexible, highly automated, easy-to-use computer program for predicting flows of rarefied gases -- especially flows of upper-atmospheric, propulsion, and vented gases impinging on spacecraft surfaces. DAC implements the direct simulation Monte Carlo (DSMC) method, which is widely recognized as standard for simulating flows at densities so low that the continuum-based equations of computational fluid dynamics are invalid. DAC enables users to model complex surface shapes and boundary conditions quickly and easily. The discretization of a flow field into computational grids is automated, thereby relieving the user of a traditionally time-consuming task while ensuring (1) appropriate refinement of grids throughout the computational domain, (2) determination of optimal settings for temporal discretization and other simulation parameters, and (3) satisfaction of the fundamental constraints of the method. In so doing, DAC ensures an accurate and efficient simulation. In addition, DAC can utilize parallel processing to reduce computation time. The domain decomposition needed for parallel processing is completely automated, and the software employs a dynamic load-balancing mechanism to ensure optimal parallel efficiency throughout the simulation.
The challenge of energy transition is immediate and immense; current projections target 75 TW of photovoltaics (PV) capacity by 2050. While any transition to renewable energy technology is preferable to the current fossil-based system, it is ideal to improve the sustainability of PV to minimize negative environmental and social impacts. Circular economy (CE) has been proposed as a method to improve the sustainability of PV, especially for emerging materials like perovskites. CE is a set of actions, principles, and systems which aim to design out waste and keep products and materials in use, to reduce environmental impacts and enable sustainable development. At the most basic level, CE is "reduce, reuse, recycle", the R-actions, in ranked order. CE of a PV technology can be metricized in a variety of ways, such as the Material Circularity Indicator (Smith and Jones, Ellen MacArthur Foundation, 2019) or recycling rates. Unfortunately, standard CE metrics have several shortcomings for measuring renewable energy technologies in the context of deployment for energy transition (Figge 2018, Saidani 2019): 1) Only measure mass flows; 2) De-prioritization of the use phase in favor of mass circularity when scoring; and 3) Tight focus on a single product scale The use phase and energy flows of PV are key to energy transition, and therefore need to be quantified. Additionally, correlating product-scale to system-scale is necessary for quantifying the environmental impacts of energy transition. Life Cycle Assessment (LCA) can address some of these concerns, but also focuses on a single product scale and has trouble capturing the dynamics of system-scale energy transition, such as the interaction of module lifetime with manufacturing demands for energy transition deployment schedules. Therefore, we developed an open-source Python-based system dynamics model to quantify the mass, energy and carbon impacts of CE R-actions for PV technologies in the energy transition; PV in the CE (PV ICE) (Ovaitt & Mirletz 2021). The tool captures supply chains from material extraction through end of life, incorporating 5 circular end of life pathways. PV ICE takes in any evolving bill of materials, module properties and deployment schedule to support researchers and decision makers with data-backed insights. In this work, we quantify and compare proposed CE sustainable PV module designs and lifecycle management strategies, spanning currently commercialized technologies, government and industry technology targets, and several low Technology Readiness Level (TRL) emerging PV technologies, including perovskites. Our analyses capture the projected evolutions of lifetime, efficiency and material circularity of these PV technologies, as well as their material supply chains. Our analyses emphasize the importance of examining a suite of metrics to identify priorities and tradeoffs, and inform design or lifecycle management decisions holistically. Previous analyses have demonstrated the central importance of PV module lifetime to support energy transition while minimizing impacts. High levels of material circularity (>90%) enable minimizing lifecycle wastes, can reduce virgin material demands if paired with improving efficiency, but demonstrate tradeoffs in energy return on investment. In the fervor of new material and technology development, it is important to remember that CE is not the end goal; decarbonization and energy transition are the end goal. CE should be used in service to improve the sustainability of PV, and R-actions evaluated for their usefulness and efficacy to this end.
The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.