PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 4: Maintenance document (version 1.1)

The Maintenance Document is a guide to the PAN AIR software system, a system which computes the subsonic or supersonic linear potential flow about a body of nearly arbitrary shape, using a higher order panel method. The document describes the over-all system and each program module of the system. Sufficient detail is given for program maintenance, updating and modification. It is assumed that the reader is familiar with programming and CDC (Control Data Corporation) computer systems. The PAN AIR system was written in FORTRAN 4 language except for a few COMPASS language subroutines which exist in the PAN AIR library. Structured programming techniques were used to provide code documentation and maintainability. The operating systems accommodated are NOS 1.2, NOS/BE and SCOPE 2.1.3 on the CDC 6600, 7600 and Cyber 175 computing systems. The system is comprised of a data management system, a program library, an execution control module and nine separate FORTRAN technical modules. Each module calculates part of the posed PAN AIR problem. The data base manager is used to communicate between modules and within modules. The technical modules must be run in a prescribed fashion for each PAN AIR problem. In order to ease the problem of supplying the many JCL cards required to execute the modules, a separate module called MEC (Module Execution Control) was created to automatically supply most of the JCL cards. In addition to the MEC generated JCL, there is an additional set of user supplied JCL cards to initiate the JCL sequence stored on the system

Enabling Personalized Process Schedules with Time-aware Process Views

Companies increasingly adopt process-aware information systems (PAISs) to model, enact, monitor, and evolve their business processes. Although the proper handling of temporal constraints (e.g., deadlines and minimum time lags between activities) is crucial for many application domains, existing PAISs vary significantly regarding the support of the temporal perspective of a business process. In previous work, we introduced characteristic time patterns for specifying the temporal perspective of PAISs. However, time-aware process schemas might be complex and hard to understand for end-users. To enable their proper visualization, therefore, this paper introduces an approach for transforming time-aware process schemas into enhanced Gantt charts. Based on this, a method for creating personalized process schedules using process views is suggested. Overall, the presented approach enables users to easily understand and monitor time-aware processes in PAISs

PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 4: Maintenance document (version 3.0)

The Maintenance Document Version 3.0 is a guide to the PAN AIR software system, a system which computes the subsonic or supersonic linear potential flow about a body of nearly arbitrary shape, using a higher order panel method. The document describes the overall system and each program module of the system. Sufficient detail is given for program maintenance, updating, and modification. It is assumed that the reader is familiar with programming and CRAY computer systems. The PAN AIR system was written in FORTRAN 4 language except for a few CAL language subroutines which exist in the PAN AIR library. Structured programming techniques were used to provide code documentation and maintainability. The operating systems accommodated are COS 1.11, COS 1.12, COS 1.13, and COS 1.14 on the CRAY 1S, 1M, and X-MP computing systems. The system is comprised of a data base management system, a program library, an execution control module, and nine separate FORTRAN technical modules. Each module calculates part of the posed PAN AIR problem. The data base manager is used to communicate between modules and within modules. The technical modules must be run in a prescribed fashion for each PAN AIR problem. In order to ease the problem of supplying the many JCL cards required to execute the modules, a set of CRAY procedures (PAPROCS) was created to automatically supply most of the JCL cards. Most of this document has not changed for Version 3.0. It now, however, strictly applies only to PAN AIR version 3.0. The major changes are: (1) additional sections covering the new FDP module (which calculates streamlines and offbody points); (2) a complete rewrite of the section on the MAG module; and (3) strict applicability to CRAY computing systems

Special Libraries, December 1977

Volume 68, Issue 12https://scholarworks.sjsu.edu/sla_sl_1977/1008/thumbnail.jp

Concepts and requirements for shuttle/payload orbital operations of the space transportation system

The results of studies and software development activities are summarized. Technical reports and memoranda are presented in a graphical history of contract activities and the expenditure of engineering manhours. Major topics and activities are: (1) flight phase standardization; (2) flight profile standardization; (3) maneuver targeting for solid rocket motors; (4) relative motion and RCS (Reaction Control System) jet flowfield plotting programs; (5) on-orbit aerodynamic models; (6) terminal approach strategy for payload retrieval/docking; (7) proximity navigation; and (8) desk-top flight simulator for proximity operations. A list of recommendations is also presented

Visualizing Large Business Process Models: Challenges, Techniques, Applications

Large process models may comprise hundreds or thousands of process elements, like activities, gateways, and data objects. Presenting such process models to users and enabling them to interact with these models constitute crucial tasks of any process-aware information systems (PAISs). Existing PAISs, however, neither provide adequate techniques for visualizing and abstracting process models nor for interacting with them. In particular, PAISs do not provide tailored process visualizations as needed in complex application environments. This paper presents examples of large process models and discusses some of the challenges to be tackled when visualizing and abstracting respective models. Further, it presents a comprehensive framework that allows for personalized process model visualizations, which can be tailored to the specific needs of the different user groups. First, process model complexity can be reduced by abstracting the models, i.e., by eliminating or aggregating process elements not relevant in the given visualization context. Second, the appearance of process elements can be customized independent of the process modeling language used. Third, different visualization formats (e.g., process diagrams, process forms, and process trees) are supported. Finally, it will be discussed how tailored visualizations of process models may serve as basis for changing and evolving process models at a high level of abstraction

A importância da adequabilidade do modelo no desempenho de cartas de controlo com risco ajustado

Várias cartas de controlo têm sido adaptadas para uma utilização mais eficiente na área da Saúde, incorporando na análise, um modelo que estima, para cada paciente, o risco de ocorrência do acontecimento que se pretende monitorizar. A adequabilidade do modelo é muito importante no delineamento destas cartas na medida em que afeta o desempenho das mesmas. Neste trabalho, estudámos o efeito do erro de estimação e predição no desempenho das cartas de controlo CUSUM adaptadas para risco ajustado

Energy refurbishment planning of Italian school buildings using data-driven predictive models

In the current practice, the design of energy refurbishment interventions for existing buildings is typically addressed by performing time-consuming software-based numerical simulations. However, this approach may be not suitable for preliminary assessment studies, especially when large building portfolios are involved. Therefore, this research work aims at developing simplified data-driven predictive models to estimate the energy consumption of existing school buildings in Italy and support the decision-making process in energy refurbishment intervention planning at a large scale. To accomplish this, an extensive database is assembled through comprehensive on-site surveys of school buildings in Southern Italy. For each school, a Building Information Modelling (BIM) model is developed and validated considering real energy consumption data. These BIM models serve in the design of suitable energy refurbishment interventions. Moreover, a comprehensive parametric investigation based on refined energy analyses is carried out to significantly improve and integrate the dataset. To derive the predictive models, firstly the most relevant parameters for energy consumption are identified by performing sensitivity analyses. Based on these findings, predictive models are generated through a multiple linear regression method. The suggested models provide an estimation of the energy consumption of the “as-built” configuration, as well as the costs and benefits of alternative energy refurbishment scenarios. The reliability of the proposed simplified relationships is substantiated through a statistical analysis of the main error indices. Results highlight that the building's shape factor (i.e., the ratio between the building's envelope area and its volume) and the area-weighted average of the thermal properties of the building envelope significantly affect both the energy consumption of school buildings and the achievable savings through retrofitting interventions. Finally, a framework for the preliminary design of energy refurbishment of buildings, based on the implementation of the herein developed predictive model, is proposed and illustrated through a worked example application. Worth noting that, while the proposed approach is currently limited to school buildings, the methodology can conceptually be extended to any building typology, provided that suitable data on energy consumption are available