DORMAN computer program (study 2.5). Volume 1: Executive summary

The DORCA Applications study has been directed at development of a data bank management computer program identified as DORMAN. Because of the size of the DORCA data files and the manipulations required on that data to support analyses with the DORCA program, automated data techniques to replace time-consuming manual input generation are required. The Dynamic Operations Requirements and Cost Analysis (DORCA) program was developed for use by NASA in planning future space programs. Both programs are designed for implementation on the UNIVAC 1108 computing system. The purpose of this Executive Summary Report is to define for the NASA management the basic functions of the DORMAN program and its capabilities

Programmatic effects of utilizing various space tug options

The results are summarized of the computerized (DORCA) analyses of a number of NASA/Non-NASA and DoD payload mission models that have been used in conjunction with studies of the Space Transportation System (STS). The first analysis performed was on the 1971 NASA/Non-NASA and DoD mission models. Subsequent to that, analyses of the June 1972 excursion to the 1971 NASA/Non-NASA mission models were performed. The mission models have two basic versions; i.e., one employing expendable payloads and another employing a best mix of expendable and reusable payloads. Both versions of the models have the same payload deployment schedule. However, in the best mix version, payloads are retrieved from orbit and whenever possible, refurbished payloads are deployed. The analyses were performed to determine the relative merits to different Tug configurations and of Tug combinations employed in several phased development schemes

Manned systems utilization analysis (study 2.1). Volume 3: LOVES computer simulations, results, and analyses

The LOVES computer program was employed to analyze the geosynchronous portion of the NASA's 1973 automated satellite mission model from 1980 to 1990. The objectives of the analyses were: (1) to demonstrate the capability of the LOVES code to provide the depth and accuracy of data required to support the analyses; and (2) to tradeoff the concept of space servicing automated satellites composed of replaceable modules against the concept of replacing expendable satellites upon failure. The computer code proved to be an invaluable tool in analyzing the logistic requirements of the various test cases required in the tradeoff. It is indicated that the concept of space servicing offers the potential for substantial savings in the cost of operating automated satellite systems

DORMAN computer program (study 2.5). Volume 3: Original data bank listing

A number of analyses have been performed using the DORCA program for several NASA-funded Aerospace Corporation studies in the past few years. The data decks containing the input data for these analyses have been compiled and are submitted, under separate cover. A few of the data decks are full (basic) decks containing every data item and are used as reference decks in the data bank. The other data decks were obtained by differencing a full deck with respect to one of the reference decks. Using the DORMAN program, a full deck can be recreated from the modified deck and its reference deck when and if desired. The content and structure of the data bank are described. A description of each of these data decks is presented. Three of the cases that are included in this volume have become so widely recognized and accepted that additional descriptive material has been provided. The three cases are: Case 500 Costs, Case 506 Costs, and Case 403

Autonomous planning tool for changeable assembly systems

Car manufacturers are expected to start series production of fuel cell vehicles within the next years. Simultaneously, other industries are pushing towards the utilization of fuel cells. Fuel cell manufacturers need to scale up production at the right time and react to changing product requirements with the ideal level and point of changeability. This complex task requires methods and tools for decision support. The authors present SkaliA, an autonomous planning tool, which generates guidelines for the efficient use of change enablers specific to an assembly system. The planning tool is demonstrated on the example of an assembly system for high pressure valves used in fuel cell applications

A variable neurodegenerative phenotype with polymerase gamma mutation

mtDNA replication and repair, causes mitochondrial diseases including autosomal dominant progressive external ophthalmoplegia (PEO),1 childhood hepato-encephalopathy (Alpers– Huttenlocher syndrome), adult-onset spinocerebellar ataxia, and sensory nerve degeneration with dysarthria and ophthalmoparesis (SANDO)

Augmented Go & See: An approach for improved bottleneck identification in production lines

Bottlenecks in production lines are often shifting and thus hard to identify. They lead to decreased output, longer throughput times and higher work in progress. Go & See is a well-established Lean practice where managers go to the shop floor to see the problems first hand. Mixed reality is a promising technology to improve transparency in complex production environments. Until recently, mixed reality applications have been very demanding in terms of computing power requiring high performance hardware. This paper presents an approach for real-time KPI visualization using mixed reality for bottleneck identification in production lines relying on the bring-your-own device principle. The developed application uses image recognition to identify work stations and visualizes cycle times and work in progress in augmented reality. With this additional information, it is possible to discern different root causes for bottlenecks, for example systematically higher or varying cycle times due to breakdowns. This solution can be classified according to the acatech industry 4.0 maturity model as a level 3 - transparency - application. It could be shown that the identification of bottlenecks and underlying reasons has been improved compared to standard Go & See

Cross-verification of independent quantum devices

Quantum computers are on the brink of surpassing the capabilities of even the most powerful classical computers. This naturally raises the question of how one can trust the results of a quantum computer when they cannot be compared to classical simulation. Here we present a verification technique that exploits the principles of measurement-based quantum computation to link quantum circuits of different input size, depth, and structure. Our approach enables consistency checks of quantum computations within a device, as well as between independent devices. We showcase our protocol by applying it to five state-of-the-art quantum processors, based on four distinct physical architectures: nuclear magnetic resonance, superconducting circuits, trapped ions, and photonics, with up to 6 qubits and 200 distinct circuits