The leading-twist pion and kaon distribution amplitudes from the QCD instanton vacuum

We investigate the leading-twist light-cone distribution amplitudes for the pion and kaon, based on the nonlocal chiral quark model from the instanton vacuum. Effects of explicit flavor SU(3)-symmetry breaking are taken into account. The Gegenbauer moments are computed, analyzed and compared with those of other models. The one-loop QCD evolution of the moments is briefly discussed. The transverse momentum distributions are also discussed for the pion and kaon light-cone wave functions.Comment: 17 pages, 12 figures. Accepted for publication in Physical Review

Documentation of the Analyses of the Benefits and Costs of Aeronautical Research and Technology models (ABC-ART). Volume 2: Appendices

Fleet variables are defined, and source codes for each module are presented

Documentation of the analysis of the benefits and costs of aeronautical research and technology models, volume 1

The analysis of the benefits and costs of aeronautical research and technology (ABC-ART) models are documented. These models were developed by NASA for use in analyzing the economic feasibility of applying advanced aeronautical technology to future civil aircraft. The methodology is composed of three major modules: fleet accounting module, airframe manufacturing module, and air carrier module. The fleet accounting module is used to estimate the number of new aircraft required as a function of time to meet demand. This estimation is based primarily upon the expected retirement age of existing aircraft and the expected change in revenue passenger miles demanded. Fuel consumption estimates are also generated by this module. The airframe manufacturer module is used to analyze the feasibility of the manufacturing the new aircraft demanded. The module includes logic for production scheduling and estimating manufacturing costs. For a series of aircraft selling prices, a cash flow analysis is performed and a rate of return on investment is calculated. The air carrier module provides a tool for analyzing the financial feasibility of an airline purchasing and operating the new aircraft. This module includes a methodology for computing the air carrier direct and indirect operating costs, performing a cash flow analysis, and estimating the internal rate of return on investment for a set of aircraft purchase prices

The Exact MSSM Spectrum from String Theory

We show the existence of realistic vacua in string theory whose observable sector has exactly the matter content of the MSSM. This is achieved by compactifying the E_8 x E_8 heterotic superstring on a smooth Calabi-Yau threefold with an SU(4) gauge instanton and a Z_3 x Z_3 Wilson line. Specifically, the observable sector is N=1 supersymmetric with gauge group SU(3)_C x SU(2)_L x U(1)_Y x U(1)_{B-L}, three families of quarks and leptons, each family with a right-handed neutrino, and one Higgs-Higgs conjugate pair. Importantly, there are no extra vector-like pairs and no exotic matter in the zero mode spectrum. There are, in addition, 6 geometric moduli and 13 gauge instanton moduli in the observable sector. The holomorphic SU(4) vector bundle of the observable sector is slope-stable.Comment: 15 pages, LaTeX; v2: Hidden sector is unstable, symbol typesetting error corrected, clarifications and references added; v3: New discussion of hidden secto

Constraining the Kahler Moduli in the Heterotic Standard Model

Phenomenological implications of the volume of the Calabi-Yau threefolds on the hidden and observable M-theory boundaries, together with slope stability of their corresponding vector bundles, constrain the set of Kaehler moduli which give rise to realistic compactifications of the strongly coupled heterotic string. When vector bundles are constructed using extensions, we provide simple rules to determine lower and upper bounds to the region of the Kaehler moduli space where such compactifications can exist. We show how small these regions can be, working out in full detail the case of the recently proposed Heterotic Standard Model. More explicitely, we exhibit Kaehler classes in these regions for which the visible vector bundle is stable. On the other hand, there is no polarization for which the hidden bundle is stable.Comment: 28 pages, harvmac. Exposition improved, references and one figure added, minor correction

Strange Particle Production from SIS to LHC

>1A review of meson emission in heavy ion collisions at incident energies from SIS up to collider energies is presented. A statistical model assuming chemical equilibrium and local strangeness conservation (i.e. strangeness conservation per collision) explains most of the observed features. Emphasis is put onto the study of $K^+$ and $K^-$ emission at low incident energies. In the framework of this statistical model it is shown that the experimentally observed equality of $K^+$ and $K^-$ rates at ``threshold-corrected'' energies $\sqrt{s} - \sqrt{s_{th}}$ is due to a crossing of two excitation functions. Furthermore, the independence of the $K^+$ to $K^-$ ratio on the number of participating nucleons observed between SIS and RHIC is consistent with this model. It is demonstrated that the $K^-$ production at SIS energies occurs predominantly via strangeness exchange and this channel is approaching chemical equilibrium. The observed maximum in the $K^+/\pi^+$ excitation function is also seen in the ratio of strange to non-strange particle production. The appearance of this maximum around 30 $A\cdot$GeV is due to the energy dependence of the chemical freeze-out parameters $T$ and $\mu_B$.Comment: Presented at the International Workshop "On the Physics of the Quark-Gluon Plasma", Palaiseau, France, September 2001. 10 pages, 8 figure

Comparing Maintenance Strategies for Rooftop Units having Multiple Faults through Simulation

Maintenance strategies currently used for commercial building rooftop units (RTU) can be classified into two categories: reactive strategies and proactive strategies. In reactive strategies, maintenance and service is performed only when needed, e.g. when a system is unable to maintain setpoint. In proactive strategies, maintenance is scheduled at routine intervals to avoid service interruptions regardless of whether the system actually needs it. While these strategies could not be more different, it is unclear which strategy is more optimal. Moreover, whether one strategy is more optimal than the other more than likely depends on the application – contributing to much uncertainty. A third category of maintenance has been enabled by automated fault detection and diagnostics (AFDD) technologies that aims to provide building operators and service providers more detailed information about the actual state of equipment in the field. This third strategy, called condition-based maintenance, aims to optimize service and maintenance decisions throughout the life of equipment based on updated measurements of performance and service costs. In this work, these three types of maintenance strategies are compared using a commercial building simulation model utilizing a fault impact equipment model. Along with comparing different strategies under the same fault scenario, ambient conditions, and loads, optimal maintenance schedules are generated using dynamic programming. Benefits of a condition-based maintenance approach utilizing a suite of AFDD methodologies are highlighted with respect to reducing operating costs

Artificial Neural Networks for Fast Rooftop Unit Fault Impact Modeling and Simulation

Like any electromechanical system, direct-expansion (DX) air conditioners and heat pumps often develop faults over time that contribute to reduced operating efficiency, more frequent comfort violations, or even premature failure. Automated fault detection and diagnosis (AFDD) methods have been developed for these systems and much experimental effort has been undertaken for their evaluation. In order to reduce development costs required for AFDD technologies, additional research related to modeling DX equipment subject to faults has been undertaken. Investigation of AFDD methods in a virtual environment typically requires relatively detailed equipment models based in some part on thermodynamic principles. Because of these embedded constraints, simulation of faulty equipment operating performance can be time consuming and computationally intensive. In this work, meta-models based on previously developed greybox fault impact models for DX equipment have been developed using artificial neural networks. After tuning these neural network meta-models for different equipment, AFDD performance and fault impacts were simulated using a simple building load model. Significant computational speedups were realized over the original greybox equipment models without loss of significant accuracy. Ultimately through careful meta-model training, it is believed that using neural networks to approximate detailed, computationally-intensive equipment or building models may be useful in applications that require frequent model evaluations

Development of an Embedded RTU FDD using Open-Source Monitoring and Control Platform

Previous research on automated fault detection and diagnostics (FDD) for HVAC systems has shown promising benefits like earlier detection and more accurate isolation of different faults. While most researchers, equipment manufacturers, and policymakers agree that HVAC system FDD is important and has the potential to reduce significant energy waste due to faulty system operation, widespread adoption of these tools has been slow. An automated fault detection and diagnosis system has been developed for packaged (rooftop) air conditioners based on the VOLTTRONTM monitoring and controls framework developed by the Department of Energy. The system implements a virtual-sensor-based FDD methodology capable of isolating common rooftop unit faults such as improper refrigerant charge level, heat exchanger fouling, liquid-line restrictions, and compressor valve leakage. A fault impact evaluation component has also been implemented in order to determine the relative impact that faults have on system performance. This is accomplished using virtual sensor outputs and manufacturers’ performance map reference models for performance indices such as cooling capacity and COP. This system has been implemented using low-cost electronics components and was be tested using a 5-ton RTU in a laboratory environment. In this work, a high-level overview of the automated rooftop unit (RTU) FDD system structure will be presented detailing how individual software agents interact along with a description of the computational and network requirements of the system. Alternative system architectures will also be discussed in comparison to the hybrid system presented. A review of the FDD algorithms is also presented that details the virtual sensors implementations along with the methodology to detect, diagnose, and evaluate different faults.  Finally, the performance of the FDD system will be demonstrated using laboratory test data collected for a 4-ton RTU with micro-channel condenser. The goal of this research is to produce a field ready FDD tool for RTUs that can be used to show the benefits of FDD in real systems. Ultimately, the software implementation (using Python) and hardware designs of all the systems components will be released under an open source license in an effort to reduce the engineering effort required by equipment manufacturers interested in a complete AFDD solution