Modeling Electricity Production-Demand Correlations for STEC Plants in Dispersed Locations

It has been a recent task of IIASA's Energy Systems Program to study solar energy and in particular opportunities for deploying large-scale solar technologies for electricity production in a set of countries. In this context the present simulation model was developed. This model called STECP was used to investigate the electrical output of solar plants with and without internal thermal storage that were conceived to be spread across three different time zones. As a result, it appears that a higher reliability of electricity supply can be achieved if the solar plants are sited in dispersed locations than if they were concentrated in one place. Introduction of internal thermal storage in the system of solar plants increases its seasonal electric output from two to three times and decreases external storage requirements. The model, which is described here along with some application results, permits a consistent investigation of the electricity production-demand correlation for a system of solar electric plants

Modeling the Utilization of Local Residues for Energy Production: An Application in the Silistra Region, Bulgaria

Developed agricultural regions generate substantial quantities of cellulose residues, which at present are only partially utilized. The remainder is destroyed, thereby damaging the environmental quality of the region, and leading to additional expenditures for environmental management. The rise in primary energy prices has recently stimulated investigations of the feasibility of converting residues into secondary energy forms such as biogas and ethanol. This paper presents an application in the Silistra region, Bulgaria, of a model for utilizing local residues for energy production. The model, developed at IIASA, is designed to assist regional decision makers in their investigations of the effects on the regional energy balance of introducing new energy-conversion installations

Decomposition of a Large-Scale Energy Model

The modeling of energy systems generally involves the solution of very large scale linear programming problems which include descriptions of the energy transformation chains. The scale of the problem and the variety of processes considered are such that the model should, ideally, be composed of submodels, each developed by experts in the appropriate field. However, this is not usually possible for a number of reasons. One of the most important of these is the absence of efficient methods for linking or making consistent the various submodels, which may be based on different time-scales and different degrees of aggregation, and which may involve different policy variables and economic agents. Another reason for the infrequent use of this modular approach may lie in the many reported failures of attempts to implement decomposition approaches in large-scale optimization systems. These considerations, combined with the practical necessity of squeezing a large-scale model into a small computer, encouraged members of the IIASA Energy Systems Group and the Systems and Decisions Sciences Program to work together on the decomposition of the IIASA energy supply model MESSAGE II. The decomposition algorithms developed as part of research on nondifferential optimization played an important role in the study. The results suggest a method of constructing an integrated system of energy models that could provide a detailed representation of the energy supply system itself and its interaction with the major energy-intensive sectors. A thorough investigation of this interaction, in terms of the energy flows represented by the linking variables, could be valuable in determining an interally consistent national energy policy

Optimal Cutting Problem

One of the tasks of the Construction office of company STOBET Ltd is to create large sheets of paper containing a lot of objects describing a building construction as tables, charts, drawings, etc. For this reason it is necessary to arrange the small patterns in a given long sheet of paper with a minimum wastage. Another task of the company is to provide a way of cutting a stock material, e.g. given standard steel rods, into different number of smaller sized details in a way that minimizes the wasted material

Gravity compensation in complex plasmas by application of a temperature gradient

Micron sized particles are suspended or even lifted up in a gas by thermophoresis. This allows the study of many processes occurring in strongly coupled complex plasmas at the kinetic level in a relatively stress-free environment. First results are presented. The technique is also of interest for technological applications.Comment: 4 pages, 4 figures, final version to be published in Phys. Rev. Let

DepQBF 6.0: A Search-Based QBF Solver Beyond Traditional QCDCL

We present the latest major release version 6.0 of the quantified Boolean formula (QBF) solver DepQBF, which is based on QCDCL. QCDCL is an extension of the conflict-driven clause learning (CDCL) paradigm implemented in state of the art propositional satisfiability (SAT) solvers. The Q-resolution calculus (QRES) is a QBF proof system which underlies QCDCL. QCDCL solvers can produce QRES proofs of QBFs in prenex conjunctive normal form (PCNF) as a byproduct of the solving process. In contrast to traditional QCDCL based on QRES, DepQBF 6.0 implements a variant of QCDCL which is based on a generalization of QRES. This generalization is due to a set of additional axioms and leaves the original Q-resolution rules unchanged. The generalization of QRES enables QCDCL to potentially produce exponentially shorter proofs than the traditional variant. We present an overview of the features implemented in DepQBF and report on experimental results which demonstrate the effectiveness of generalized QRES in QCDCL.Comment: 12 pages + appendix; to appear in the proceedings of CADE-26, LNCS, Springer, 201

QRAT+: Generalizing QRAT by a More Powerful QBF Redundancy Property

The QRAT (quantified resolution asymmetric tautology) proof system simulates virtually all inference rules applied in state of the art quantified Boolean formula (QBF) reasoning tools. It consists of rules to rewrite a QBF by adding and deleting clauses and universal literals that have a certain redundancy property. To check for this redundancy property in QRAT, propositional unit propagation (UP) is applied to the quantifier free, i.e., propositional part of the QBF. We generalize the redundancy property in the QRAT system by QBF specific UP (QUP). QUP extends UP by the universal reduction operation to eliminate universal literals from clauses. We apply QUP to an abstraction of the QBF where certain universal quantifiers are converted into existential ones. This way, we obtain a generalization of QRAT we call QRAT+. The redundancy property in QRAT+ based on QUP is more powerful than the one in QRAT based on UP. We report on proof theoretical improvements and experimental results to illustrate the benefits of QRAT+ for QBF preprocessing.Comment: preprint of a paper to be published at IJCAR 2018, LNCS, Springer, including appendi

Entanglement Measures for Single- and Multi-Reference Correlation Effects

Electron correlation effects are essential for an accurate ab initio description of molecules. A quantitative a priori knowledge of the single- or multi-reference nature of electronic structures as well as of the dominant contributions to the correlation energy can facilitate the decision regarding the optimum quantum chemical method of choice. We propose concepts from quantum information theory as orbital entanglement measures that allow us to evaluate the single- and multi-reference character of any molecular structure in a given orbital basis set. By studying these measures we can detect possible artifacts of small active spaces.Comment: 14 pages, 4 figure

Population of isomers in decay of the giant dipole resonance

The value of an isomeric ratio (IR) in N=81 isotones ($^{137}$Ba, $^{139}$Ce, $^{141}$Nd and $^{143}$Sm) is studied by means of the ($\gamma, n)$ reaction. This quantity measures a probability to populate the isomeric state in respect to the ground state population. In ($\gamma, n)$ reactions, the giant dipole resonance (GDR) is excited and after its decay by a neutron emission, the nucleus has an excitation energy of a few MeV. The forthcoming $\gamma$ decay by direct or cascade transitions deexcites the nucleus into an isomeric or ground state. It has been observed experimentally that the IR for $^{137}$Ba and $^{139}$Ce equals about 0.13 while in two heavier isotones it is even less than half the size. To explain this effect, the structure of the excited states in the energy region up to 6.5 MeV has been calculated within the Quasiparticle Phonon Model. Many states are found connected to the ground and isomeric states by $E1$, $E2$ and $M1$ transitions. The single-particle component of the wave function is responsible for the large values of the transitions. The calculated value of the isomeric ratio is in very good agreement with the experimental data for all isotones. A slightly different value of maximum energy with which the nuclei rest after neutron decay of the GDR is responsible for the reported effect of the A-dependence of the IR.Comment: 16 pages, 4 Fig

Accurate ab initio spin densities

We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys. 2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CASCI-type wave function provides insights into chemically interesting features of the molecule under study such as the distribution of $\alpha$- and $\beta$-electrons in terms of Slater determinants, CI coefficients, and natural orbitals. The methodology is applied to an iron nitrosyl complex which we have identified as a challenging system for standard approaches [J. Chem. Theory Comput. 2011, 7, 2740].Comment: 37 pages, 13 figure