BIM and forecasting deformations in monitoring structures

BIM technologies are becoming more widely used, mainly in the design and operation of buildings and structures, and in most cases this is enough for trouble-free operation. Nevertheless, there is a category of buildings for which the monitoring of the technical condition should be an integral part of the construction and operation. These are the so-called public large-span structures. Unfortunately, the development of BIM technology in the Russian Federation is not at such a level as to answer questions about the behaviour of objects under changing environmental conditions and reveal hidden patterns in the monitoring data. Based on the analysis of literary sources, the authors reviewed various methods for identifying hidden patterns in geodetic measurement data when monitoring buildings and structures. It is noted that modern analysis methods are based on statistical processing of measurement results and on the statistical method of forecasting. However, there are attempts to apply models that take into account the design features and the temperature regime of the object. This type includes the two proposed models, which are used to model the three-dimensional coordinates of the strain marks in the 3D model and only the elevations of the marks in the 1-Z model. The article presents the rationale for the simulated geometric elements and properties of the object. The solution of the equations of both models and the analysis of the results and parameters of the model for measurement epochs are shown. The simulation is shown on the example of a real object, which was monitored by the authors in 2015-2016. The authors believe that the monitoring of large-span structures and the search for patterns of their behaviour should be an integral part of the BIM system for such structures

The Parallelism Motifs of Genomic Data Analysis

Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share this data with the research community, but some of these genomic data analysis problems require large scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high end parallel systems today and place different requirements on programming support, software libraries, and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high performance genomics analysis, including alignment, profiling, clustering, and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or motifs that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing

Cache-Aware Memory Manager for Optimistic Simulations

Parallel Discrete Event Simulation is a well known technique for executing complex general-purpose simulations where models are described as objects the interaction of which is expressed through the generation of impulsive events. In particular, Optimistic Simulation allows full exploitation of the available computational power, avoiding the need to compute safety properties for the events to be executed. Optimistic Simulation platforms internally rely on several data structures, which are meant to support operations aimed at ensuring correctness, inter-kernel communication and/or event scheduling. These housekeeping and management operations access them according to complex patterns, commonly suffering from misuse of memory caching architectures. In particular, operations like log/restore access data structures on a periodic basis, producing the replacement of in-cache buffers related to the actual working set of the application logic, producing a non-negligible performance drop. In this work we propose generally-applicable design principles for a new memory management subsystem targeted at Optimistic Simulation platforms which can face this issue by wisely allocating memory buffers depending on their actual future access patterns, in order to enhance event-execution memory locality. Additionally, an application-transparent implementation within ROOT-Sim, an open-source generalpurpose optimistic simulation platform, is presented along with experimental results testing our proposal

Software Design Guidelines for Usability

For years, the Human Computer Interaction (HCI) community has crafted usability guidelines that clearly define what
characteristics a software system should have in order to be easy to use. However, in the Software Engineering (SE)
community keep falling short of successfully incorporating these recommendations into software projects. From a SE
perspective, the process of incorporating usability features into software is not always straightforward, as a large number
of these features have heavy implications in the underlying software architecture. For example, successfully including an
“undo” feature in an application requires the design and implementation of many complex interrelated data structures and
functionalities. Our work is focused upon providing developers with a set of software design patterns to assist them in the
process of designing more usable software. This would contribute to the proper inclusion of specific usability features
with high impact on the software design. Preliminary validation data show that usage of the guidelines also has positive
effects on development time and overall software design quality

Integrating a universal query mechanism into java

This thesis discusses design, architecture, and application of a universal query language embedded in Java. Utilizing various design patterns and Java\u27s polymorphism, the current result is a preprocessor that will convert an embedded language into compilable Java. The resulting Java utilizes a back{end developed for the queried data structure, capable of querying that structures internal data

Big Data Dimensional Analysis

The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity and variety. One of the main challenges associated with big data variety is automatically understanding the underlying structures and patterns of the data. Such an understanding is required as a pre-requisite to the application of advanced analytics to the data. Further, big data sets often contain anomalies and errors that are difficult to know a priori. Current approaches to understanding data structure are drawn from the traditional database ontology design. These approaches are effective, but often require too much human involvement to be effective for the volume, velocity and variety of data encountered by big data systems. Dimensional Data Analysis (DDA) is a proposed technique that allows big data analysts to quickly understand the overall structure of a big dataset, determine anomalies. DDA exploits structures that exist in a wide class of data to quickly determine the nature of the data and its statical anomalies. DDA leverages existing schemas that are employed in big data databases today. This paper presents DDA, applies it to a number of data sets, and measures its performance. The overhead of DDA is low and can be applied to existing big data systems without greatly impacting their computing requirements.Comment: From IEEE HPEC 201

Integration of CFD Methods into Concurrent Design of Internal Combustion Engine

This paper describes patterns of algorithms for different innovative levels of design at parametric, configuration and conceptual levels. They can be applied to Computer-aided Engine Design (CED). Data structures, process simulation hierarchy, engine simulation modules and the requirements for further development are described. An example of advanced thermodynamics modeling of combustion engines is included