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Numerical analyses of transitions between restricted problem of three bodies and problem of two fixed centers and Kepler problem
Equivalence of optimal control problems and transformation of optimal control problems with compact control regions into Lagrange problems
There are two common ways to evaluate algorithms: performance on benchmark problems derived from real applications and analysis of performance on parametrized families of problems. The two approaches complement each other, each having its advantages and disadvantages. The planning community has concentrated on the first approach, with few ways of generating parametrized families of hard problems known prior to this work. Our group's main interest is in comparing approaches to solving planning problems using a novel type of computational device - a quantum annealer - to existing state-of-the-art planning algorithms. Because only small-scale quantum annealers are available, we must compare on small problem sizes. Small problems are primarily useful for comparison only if they are instances of parametrized families of problems for which scaling analysis can be done. In this technical report, we discuss our approach to the generation of hard planning problems from classes of well-studied NP-complete problems that map naturally to planning problems or to aspects of planning problems that many practical planning problems share. These problem classes exhibit a phase transition between easy-to-solve and easy-to-show-unsolvable planning problems. The parametrized families of hard planning problems lie at the phase transition. The exponential scaling of hardness with problem size is apparent in these families even at very small problem sizes, thus enabling us to characterize even very small problems as hard. The families we developed will prove generally useful to the planning community in analyzing the performance of planning algorithms, providing a complementary approach to existing evaluation methods. We illustrate the hardness of these problems and their scaling with results on four state-of-the-art planners, observing significant differences between these planners on these problem families. Finally, we describe two general, and quite different, mappings of planning problems to QUBOs, the form of input required for a quantum annealing machine such as the D-Wave II.
NASA's AATT Program is investigating potential ground-based decision support tool (DST) development for en route controllers and managers. NASA's previous work in en route DST development has focused on Transition airspace, where aircraft are impacted by constraints associated with the transition of aircraft from en route to terminal airspace. This paper investigates the problems associated with aircraft in non-transitional en route airspace, termed Constrained Airspace. A literature search was performed to catalog previously identified constrained airspace problems. The results of this search were investigated with industry representatives to validate these problems were significant in constrained airspace. Three general problem areas were identified. The first problem area involves negative impacts caused by a loss of airspace (e.g., activation of Special Use Airspace (SUA), weather cell formation, and overloaded sectors). The second problem area is the lack of identifying and taking advantage of gained airspace (e.g., SUA deactivation, weather dissipation, and sector loading reductions). The third problem area is unforeseen negative impacts caused by the acceptance of user routing requests (e.g., a route change into an area of congestion that negated the users intended benefit). Based upon the problems identified, an operational concept was developed for a DST to help handle these problems efficiently. The goal is to strategically identify constrained airspace problems and to provide functionality to support ARTCC TMUs in resolving the identified impacts. The capability lends itself well to TMU and Airline Operations Center (AOC) collaboration.
The restricted Three-Body-Problem considers the motion of an infinitesimal mass under the gravitational attraction of two finite masses, which revolve about their common center of gravity in coplanar circles. It is well known that Euler's problem of two fixed centers, consisting of the motion of an infinitesimal mass under the gravitational attraction of two finite masses fixed in space, can be solved by elliptic functions. The idea presented here is to take the solution of Euler's problem as the solution of the restricted Three-Body-Problem by allowing the initial values to be functions of time now. Differential equations for the perturbed initial values are established. These equations can be given in closed form by using the fact that the transformation to the perturbed initial values of Euler's problem is canonical. Thus, an approximation can be obtained for the solution of the restricted Three-Body-Problem. The method can also be used to represent classes of neighboring trajectories for guidance purposes.
We introduce the Swath Segment Selection problem (SSSP). The SSSP consists of a constrained geometric covering problem and a capacitated resource problem. It comes from the real-life problem of scheduling on- and off-times for air or space-borne instruments that image a target by flying over and collecting a swath of information.
A theory for obtaining approximate solutions to nonlinear problems whose exact solutions require the use of large computational procedures is described. The technique represents in some respects a generalization of the method of base and comparison solutions for flows depending on a parameter. For the generalized problem, the input variable is no longer a parameter but a function that is incremented over its entire domain. After performing calculations for a base configuration and a small number of variations of it, solutions for a large class of configurations can be obtained by forming linear combinations of the solution increments. For a restricted class of problems, approximate solutions can be obtained for general variations of a base configuration by using a function-space derivative estimate obtained from a base solution and a single variation.
We present MENDER, a knowledge based system that implements software design techniques that are specialized to automatically compile generate-and-patch problem solvers that satisfy global resource assignments problems. We provide empirical evidence of the superior performance of generate-and-patch over generate-and-test: even with constrained generation, for a global constraint in the domain of '2D-floorplanning'. For a second constraint in '2D-floorplanning' we show that even when it is possible to incorporate the constraint into a constrained generator, a generate-and-patch problem solver may satisfy the constraint more rapidly. We also briefly summarize how an extended version of our system applies to a constraint in the domain of 'multiprocessor scheduling'.
Restricted three-body problem is solved using solutions of eulers problem of two fixed centers
Two-center problem orbit as intermediate orbit for restricted three-body problem
Three body problem zero velocity curves - euler two center problem by graphical analysis - guidance systems
Lagrange problems with variable endpoint as optimal control problems
Transforming optical control problem into equivalent Lagrange problem in calculus of variations
The progressive realization of the consequences of nonuniqueness imply an evolution of both the methods and the centers of interest in inverse problems. This evolution is schematically described together with the various mathematical methods used. A comparative description is given of inverse methods in scientific research, with examples taken from mathematics, quantum and classical physics, seismology, transport theory, radiative transfer, electromagnetic scattering, electrocardiology, etc. It is hoped that this paper will pave the way for an interdisciplinary study of inverse problems.
The overheating problem, first observed by von Neumann [1] and later studied extensively by Noh [2] using both Eulerian and Lagrangian formulations, remains to be one of the unsolved problems by shock capturing. It is historically well known to occur when a flow is under compression, such as when a shock wave hits and reflects from a wall or when two streams collides with each other. The overheating phenomenon is also found numerically in a smooth flow undergoing rarefaction created by two streams receding from each other. This is in contrary to one s intuition expecting a decrease in internal energy. The excessive amount in the temperature increase does not reduce by refining the mesh size or increasing the order of accuracy. This study finds that the overheating in the receding flow correlates with the entropy generation. By requiring entropy preservation, the overheating is eliminated and the solution is grid convergent. The shock-capturing scheme, as being practiced today, gives rise to the entropy generation, which in turn causes the overheating. This assertion stands up to the convergence test.
Perturbation theory of two-fixed-center problem leading to restricted three-body approximation
Three body problem by hamilton-jacobi perturbation theory - guidance systems
Numerical residual perturbation solution for prediction of satellite position in restricted three-body problem