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Eigenvalue approximation method for non-self-adjoint operators using Galerkin method for estimating eigenvalue perturbations of self-adjoint operators
The effects of different methods of approximating multispecies transport phenomena in models of premixed, laminar, steady state flames were studied. Five approximation methods that span a wide range of computational complexity were developed. Identical data for individual species properties were used for each method. Each approximation method is employed in the numerical solution of a set of five H2-02-N2 flames. For each flame the computed species and temperature profiles, as well as the computed flame speeds, are found to be very nearly independent of the approximation method used. This does not indicate that transport phenomena are unimportant, but rather that the selection of the input values for the individual species transport properties is more important than the selection of the method used to approximate the multispecies transport. Based on these results, a sixth approximation method was developed that is computationally efficient and provides results extremely close to the most sophisticated and precise method used.
Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.
Successive approximation method for solution to differential equation system
An error bound is derived for a reliability model approximation method. The approximation method is appropriate for the semi-Markov models of reconfigurable systems that are designed to achieve extremely high reliability. The semi-Markov models of these system are complex, and a significant amount of their complexity arises from the detailed descriptions of the reconfiguration processes. The reliability model approximation method consists of replacing a detailed description of a reconfiguration process with the probabilities of the possible outcomes of the reconfiguration process. These probabilities are included in the model as instantaneous jumps from the fault-occurrence state. Since little time is spent in the reconfiguration states, instantaneous jumps are a close approximation to the original model. This approximation procedure is shown to produce an overestimation for the probability of system failure, and an error bound is derived for this overestimation.
Approximate solutions to fluid dynamics and heat transfer problems by variational technique based on least squares method
Noniterative integral-entrainment method yields good approximations. Method of approximate calculation of flow in channel of turbomachine based on interaction of viscous flow in boundary layers with inviscid flow in core layer. Faster and more robust than other approximate methods of same type. Suitable for use in preliminary calculations for design and for off-design operation of turbomachinery. Flows in conical diffuser channels represented by two-dimensional boundary-layer and one-dimensional core flows described by equations of new method.
Approximation concepts and dual methods are extended to solve structural synthesis problems involving a mix of discrete and continuous sizing type of design variables. Pure discrete and pure continuous variable problems can be handled as special cases. The basic mathematical programming statement of the structural synthesis problem is converted into a sequence of explicit approximate primal problems of separable form. These problems are solved by constructing continuous explicit dual functions, which are maximized subject to simple nonnegativity constraints on the dual variables. A newly devised gradient projection type of algorithm called DUAL 1, which includes special features for handling dual function gradient discontinuities that arise from the discrete primal variables, is used to find the solution of each dual problem. Computational implementation is accomplished by incorporating the DUAL 1 algorithm into the ACCESS 3 program as a new optimizer option. The power of the method set forth is demonstrated by presenting numerical results for several example problems, including a pure discrete variable treatment of a metallic swept wing and a mixed discrete-continuous variable solution for a thin delta wing with fiber composite skins.
Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.
Method of approximating propellant requirements of low thrust trajectories
Quantum-chemical computational methods are benchmarked for their ability to describe conical intersections in a series of organic molecules and models of biological chromophores. Reference results for the geometries, relative energies, and branching planes of conical intersections are obtained using ab initio multireference configuration interaction with single and double excitations (MRCISD). They are compared with the results from more approximate methods, namely, the state-interaction state-averaged restricted ensemble-referenced Kohn-Sham method, spin-flip time-dependent density functional theory, and a semiempirical MRCISD approach using an orthogonalization-corrected model. It is demonstrated that these approximate methods reproduce the ab initio reference data very well, with root-mean-square deviations in the optimized geometries of the order of 0.1 Å or less and with reasonable agreement in the computed relative energies. A detailed analysis of the branching plane vectors shows that all currently applied methods yield similar nuclear displacements for escaping the strong non-adiabatic coupling region near the conical intersections. Our comparisons support the use of the tested quantum-chemical methods for modeling the photochemistry of large organic and biological systems.
Approximation theory for Lyapunov and Sacker–Sell spectra based upon QR techniques is used to analyze the stability of a one-step method solving a time-dependent (nonautonomous) linear ordinary differential equation (ODE) initial value problem in terms of the local error. Integral separation is used to characterize the conditioning of stability spectra calculations. The stability of the numerical solution by a one-step method of a nonautonomous linear ODE using real-valued, scalar, nonautonomous linear test equations is justified. This analysis is used to approximate exponential growth/decay rates on finite and infinite time intervals and establish global error bounds for one-step methods approximating uniformly, exponentially stable trajectories of nonautonomous and nonlinear ODEs. A time-dependent stiffness indicator and a one-step method that switches between explicit and implicit Runge–Kutta methods based upon time-dependent stiffness are developed based upon the theoretical results.
Approximate solution to nonlinear differential equation of third order with bogolyubov asymptotic method
Approximation concepts and dual method algorithms are combined to create a method for minimum weight design of structural systems. Approximation concepts convert the basic mathematical programming statement of the structural synthesis problem into a sequence of explicit primal problems of separable form. These problems are solved by constructing explicit dual functions, which are maximized subject to nonnegativity constraints on the dual variables. It is shown that the joining together of approximation concepts and dual methods can be viewed as a generalized optimality criteria approach. The dual method is successfully extended to deal with pure discrete and mixed continuous-discrete design variable problems. The power of the method presented is illustrated with numerical results for example problems, including a metallic swept wing and a thin delta wing with fiber composite skins.
The unsteady form of the full potential equation is solved in conservation form, using implicit methods based on approximate factorization and relaxation schemes. A local time linearization for density is introduced to enable solution to the equation in terms of phi, the velocity potential. A novel flux-biasing technique is applied to generate proper forms of the artificial viscosity, to treat hyperbolic regions with shocks and sonic lines present. The wake is properly modeled by accounting not only for jumps in phi, but also for jumps in higher derivatives of phi obtained from requirements of density continuity. The far field is modeled using the Riemann invariants to simulate nonreflecting boundary conditions. Results are presented for flows over airfoils, cylinders, and spheres. Comparisons are made with available Euler and full potential results.
Neutron fluence, or accumulative neutron fluence rate, is a key parameter of the neutron irradiation resistance of materials (Wagner, Bergner et al. 2016). So we must try to obtain it during irradiation experiments. Neutron fluence is defined as the time integral of neutron fluence rate. To get the quantity, or to do this integral, we need to know how neutron fluence rate varied with time. The integral might not be difficult when we conduct a material irradiation experiment, because we can put certain kind of neutron detectors in the location of species, to measure neutron fluence rate (Tanaka, Endo et al. 2011). At this circumstance, the reactor power is usually maintained to be constant (Ferroukhi, Hollard et al. 2009; Dupre, Vasiliev et al. 2015). So the neutron fluence is equal to the product of neutron fluence rate and irradiation time. However, it's not the same case when we want to get the neutron fluence of structure materials used in the SPRR- 300 (Swimming Pool Research Reactor -300). This reactor is a light-water-moderated, enriched-uranium-fueled research reactor developed by China. Structural materials, such as graphite, are of great value for research (Asamoah, Gyampo et al. 2012). Graphite was used as reflector in reactor. It is a waste of material and a waste of money to dismantle it simply. However, to reuse post-irradiation graphite assemblies faces some challenges, such as neutron fluence calculation, radiation protection, etc. The former will be discussed in this paper, whereas the latter will remain to be studied for the following time. The problem is how to acquire neutron fluence distribution in structure materials, since specific measurement of neutron fluence rate were not conducted intentionally during historical reactor operation. So we need to figure it out by a method of calculation. Considering a large number of reactor refueling, we propose an approximate method, Core Combination Method of Approximation (CCMA), to calculate accumulative neutron fluence rate of key structure materials during a long period of irradiation time.
The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.