Performance Analysis Environment Research Articles

Thermal performance analysis and thermal environment creates effect of a novel solar hot-air phase change bed

Comprehensive heating provides a comfortable indoor but consumes significant energy. Temporal-spatial partitioned heating can meet differentiated thermal demands while reducing energy consumption. A novel solar hot-air phase change bed heating system has been proposed for achieving temporal-spatial partitioned heating. Theoretical analysis models have been established to study the heat transfer process of the hot-air phase change heating bed, and numerical simulations have been conducted to analyze its thermal performance and creation of a comfortable environment. The results demonstrate that at the end of the heat storage, the bed board temperature increased by 1.5 °C for every 5 °C increase in the wind temperature. The maximum temperature difference of the bed board reached 6.1 °C under three different wind speed schemes. During heat release, the bed board heat flux was affected by the phase change material heat storage difference, and the maximum temperature difference of the bed board reached 4.3 °C ∼ 6.7 °C under different schemes. After the first cycle, both indoor and bed board temperature were higher than the initial values. During the daytime, there was excessive heat indoors, and the maximum environmental temperature exceeded the comfortable range by 8.7 °C. At night, the bed was covered with a high-temperature layer, and the bed surface temperature was uniformly distributed, remaining in the thermal comfort zone for 3.8 h to 5.1 h. The research results provide a basis and guidance for utilizing solar hot-air phase change beds to improve differentiated thermal demands.

A hybrid spatial model based on identified conditions for 3D pore pressure estimation

Accurate spatial modeling of pore pressure helps to provide extensive and continuous information regarding the insightful downhole geological environment for safe drilling plans, performance analysis, and efficient reservoir modeling. Considering the varying drilling depth and pore pressure of study wells, a hybrid spatial modeling method is developed to estimate the pore pressure of an area. The method comprises three parts. In the first part, an appropriate number of pressure conditions is determined adaptively based on quantization error modeling (QEM), and similar pressure conditions are identified based on fuzzy c-means (FCM) method. In the second part, a kriging interpolation (Kriging) algorithm is introduced to produce profiles of different pressure subspaces. Afterward, random forest (RF) submodels are built separately according to the pressure profiles. In the last part, all of these submodels coalesced into one whole model. Verification of the proposed method is carried out on real case studies using field data from Songliao basin. The results show that the proposed method achieves the best prediction accuracy than the other five well-known methods for six wells, especially for well XS3, the mean absolute error and mean absolute percentage error of the proposed method achieve 0.717 and 6.063, which are at least 31% less than those of other five well-known methods.

Simulation environment for scalability and performance analysis in hierarchically organized IoT systems

The accelerated development of technologies, especially in the field of telecommunications, ease the integration of embedded devices within various IoT applications. Modern IoT applications assume heterogenous embedded platforms capable of collecting, processing, and exchanging data between the tiers of the IoT system architecture. Designing a multi-tier IoT system, even in the case of architecture that involves a small number of intelligent embedded devices, can be a very demanding process, especially when dealing with the strict requirements of IoT application concerning application performance, scalability, and energy consumption. In this paper, an open-source simulation framework for the performance analysis of an arbitrary multi-tiered IoT system is presented. Framework supports insight into the data availability within the tiers of IoT system enabling designers to evaluate the performance of IoT application and to engineer the system operation and deployment. Besides the performance analysis, proposed framework enables the analysis of energy consumption, architecture scalability utilizing different communication patterns and technologies. The case study of a large-scale IoT application for demonstrating the framework potential regarding the scalability and data availability analysis is also given.

Methodology for optimal design and control of wind energy system based on simplifying assumptions

The study presented in this paper concerns the development of a new methodology for design and controlling a wind energy generation chain. This methodology is based on combined Analytical-Finite Element-Experimental method. This type of converter chosen is an AC-DC inverter with IGBTs to improve the robustness of the power chain structure. It offers a reduction of the cost of the power chain and the improvement of the performances of the global studied system, as the control at power factor equal to unity and providing an electromagnetic torque which is added to the useful torque in order to extract the maximal energy. The control algorithms permit to regulate Le charging voltage and current in their rated values considered as optimal battery charging voltage and current. The global model of the power chain is implemented under the Matlab-Sumilink simulation environment for performance and efficiency analysis.

Designing computer-assisted problem-based learning (CAPBL) environment for performance analysis of isolation forest algorithm

Anomaly detection is important applied in various fields of application to determine errors in the system. By detecting it can minimize losses on the system. Anomaly detection can be done using several algorithms. One such algorithm is the Isolation Forest algorithm. Isolation Forest Algorithm is an efficient and effective algorithm in detecting anomalies. Isolation Forest has better performance than other algorithms in terms of execution time, especially in large datasets. Although the Isolation Forest algorithm has many advantages, there are still very few tools that provide this algorithm. One tool that provides the Isolation Forest algorithm is Scikit Learn. However, using special tools such as Scikit Learning requires sufficient time and experience to be able to manage the features of the tool. Thus, in this study the authors developed a web-based application that is used to assist users in assisting and improving the performance of Isolation Forests by using sample data sets, setting the parameters of Isolation Forests, visualization, and evaluation. This application was developed using the waterfall process model and CAPBL concept. In determining the features of the application, an analysis of features is based on the CAPBL concept with the business process of CRISP-DM. The software testing result shows that this application is fit to be used as a new solution to facilitate users who want to learn and analyze the performance of Isolation Forest.

Target Signal Simulation in Synthetic Underwater Environment for Performance Analysis of Monostatic Active Sonar

능동소나는 일반적으로 천해에서 존재하는 표적을 탐지하기 위해 사용된다. 신호가 송신되고 표적으로부터 반향되어 되돌아올 때, 표적 반향신호는 다중경로, 거친 해저면 또는 해수면에 의한 산란 그리고 음속구조에 의한 굴절과 같은 다양한 음파전달 특성에 의해 왜곡 되어 수신되며, 이는 표적 탐지를 어렵게 만든다. 그러므로 능동소나의 운용성능 체계에서 표적 신호 모의 시 음파전달 특성을 고려하는 것이 필요하다. 본 논문에서는 단상태 능동소나 시스템을 고려하였으며, 표적 반향, 잔향음 그리고 주변소음은 각각 시계열 함수로 모의되었다. 마지막으로 전체 수신 신호를 모의하기 위해 위 신호들을 합하였다. 표적의 특징(형태, 위치, 자세각 등)을 반영한 3차원 대표반향점 모델은 음원과 표적 사이에 각각의 다중경로를 고려하여 표적 반향 신호를 모의하였다. 본 논문의 결과는 표적 신호 모의 시 직접파만을 고려한 알고리즘의 결과와 비교하였다. Active sonar has been commonly used to detect targets existing in the shallow water. When a signal is transmitted and returned back from a target, it has been distorted by various properties of acoustic channel such as multipath arrivals, scattering from rough sea surface and ocean bottom, and refraction by sound speed structure, which makes target detection difficult. It is therefore necessary to consider these channel properties in the target signal simulation in operational performance system of active sonar. In this paper, a monostatic active sonar system is considered, and the target echo, reverberation, and ambient noise are individually simulated as a function of time, and finally summed to simulate a total received signal. A 3-dimensional highlight model, which can reflect the target features including the shape, position, and azimuthal and elevation angles, has been applied to each multipath pair between source and target to simulate the target echo signal. The results are finally compared to those obtained by the algorithm in which only direct path is considered in target signal simulation.

CHAMPS-Multizone—A combined heat, air, moisture and pollutant simulation environment for whole-building performance analysis

A computer simulation tool, named “CHAMPS-Multizone,” is introduced in this article for analyzing both energy and indoor air quality (IAQ) performance of buildings. The simulation model accounts for the dynamic effects of outdoor climate conditions (solar radiation, wind speed and direction, and contaminant concentrations), building materials and envelope system design, multi-zone air and contaminant flows in buildings, internal heat and pollutant sources, and operation of the building HVAC systems on the building performance. It enables combined analysis of building energy efficiency and indoor air quality. The model also has the ability to input building geometry data and HVAC system operation related information from software, such as SketchUp and DesignBuilder via IDF file format. A “bridge” to access static and dynamic building data stored in a “Virtual Building” database is also developed, allowing convenient input of initial and boundary conditions for the simulation and for comparisons between the predicted and measured results. This article summarizes the mathematical models, adopted assumptions, methods of implementation, and verification and validation results. The needs and challenges for further development are also discussed.

Special Issue: Scalable Tools for High‐end Computing

Current high-end parallel systems consist of hundreds of thousands of compute cores arranged in a complex hierarchical structure; future systems will have millions of cores. Systems, such as the Altix 4700, Blue Gene, Roadrunner, and Cray XT5, deploy multiple compute cores (homogeneous or heterogeneous) with multiple levels of shared and private caches within a processor, clustered into SMP nodes and coupled via a communication network to large-scale distributed systems. The development of efficient programs is extremely complex since the architectural details are exposed to the programmer. Productive use of such machines requires highly scalable programming tools for debugging, performance analysis, and fault tolerance. In addition, new programming models might significantly facilitate the task of the programmer. This special issue of Concurrency and Computation: Practice and Experience is devoted to programming tools that facilitate the development of efficient programs for such large-scale architectures. It is a collection of the best papers submitted to the international workshop on Scalable Tools for High-end Computing (STHEC 2008) that was held in conjunction with the International Conference on Supercomputing on June 7th on the Greek Island Kos. The papers present state-of-the-art tools for performance analysis and checkpointing on those machines. Performance analysis tools use measurements gathered during the execution of the application to detect portions of the code that can be further improved. Thus, they have to be able to cope with the large number of processors. Tools for checkpointing provide the possibility to restart an application in the case of a system failure; they have to be able to handle large number of cores as well. The selected papers present different techniques for building tools that will scale to thousands of cores. HPCToolkit 1 is a profiling-based performance analysis environment presenting the data in close relation to the source code without requiring an instrumentation of the source code. Scalasca 2 performs a parallel replay of the execution on the application's processors to find performance bottlenecks automatically. The combination of TAU and MRNet 3 provides a scalable infrastructure to offload performance data. Establishing the overlay network requires no added support from the job manager or application. Periscope 4 is based on a network of analysis agents that performs an online analysis of the application's performance behavior. When the application is started, additional processors can be allocated for the analysis agents to scale the analysis. CPPC 5 is a tool for portable checkpointing of message-passing applications. It consists of a runtime library and a compiler that assists the user by performing time-consuming tasks, such as data flow and communications analyses as well as code instrumentation. We would like to thank the authors for their excellent contributions to this special issue. We hope that it inspires future research in tools that support programmers of high-end systems in the development of efficient programs.

A simulation environment for performance analysis of HVAC systems

Due to the lack of a building simulation program that can simulate in details the combined heat, vapor, and liquid transfer in porous elements and the HVAC (heating, ventilation and air-conditioning) systems, a flexible computational algorithm has been elaborated in order to integrate models for both HVAC systems and multizone hygrothermal building model. In the algorithm, models for the primary system-composed of chiller, cooling tower, primary pumps, and condensation pumps—have been described. For the secondary system, models for the cooling and dehumidifying coil, humidifier, fan, and mixing box have been considered. Those mathematical models have been integrated into the whole-building PowerDomus simulation environment. The simulation environment is presented, and results show the usability aspects of the proposed computer environment by comparing air- and water-cooled equipment.

Modelling and performance evaluation of mobile multimedia systems using QoS-GSPN

Quality of Service (QoS) measurement of multimedia applications is one of the most important issues for call handoff and call admission control in mobile networks. Based on the QoS measures, we propose a Generalized Stochastic Petri Net (GSPN) based model, called QoS-GSPN, which can express the real-time behavior of QoS measurement for mobile networks. QoS-GSPN performance analysis methodology includes the formal expression and performance analysis environment. It offers the promise of providing real-time behavior predictability for systems characterized by substantial stochastic behavior. With this methodology we model and analyze the call handoff and call admission control schemes in the different multimedia traffic environments of a mobile network. The results of simulation experiments are used to verify the optimal performance achievable for these schemes under the QoS constraints in the given setting of design parameters.

Performance Technology for Complex Parallel and Distributed Systems

The ability of performance technology to keep pace with the growing complexity of parallel and distributed systems will depend on robust performance frameworks that can at once provide system-specific performance capabilities and support high-level performance problem solving. The TAU system is offered as an example framework that meets these requirements. With a flexible, modular instrumentation and measurement system, and an open performance data and analysis environment, TAU can target a range of complex performance scenarios. Examples are given showing the diversity of TAU application.

Integrated Environment for Power Plant Performance Analysis and Control Design

An integrated environment for power plant performance analysis and control desicn is proposed in this paper which integrates modelling, simulation analysis, optimisation design and test in one suite. Object-oriented modelling techniques provide a modular structure for repraenting plant components, which are linked by ‘flow vedon’ to constitute plant models. Algorithms for reducing algebraic loops are included, and the whole system constitutes a convenient tool for the development of power plant controllers. A hybrid sbnulator representing a real power plant can be used to test actual controllers. Analysis and design examples show the effectiveness of the environment

Design and Implementation of a Composite Performance Evaluation Model for Heterogeneous Network Management Applications

AbstractThis article examines the place of analytical models in realtime performance management applications. The main objectives are to define, specify and implement a system based on a composite model that provides the optimal software environment for performance analysis and tuning of heterogeneous networks.

A microcode-based environment for noninvasive performance analysis

We have developed an environment which allows us to collect data for performance analysis by modifying the microcode of a VAX 8600. This use of microprogramming permits data to be collected with minimal system perturbation (i.e. the data is almost as good as that obtained with a hardware monitor) but at the cost and with the ease of use of a software simulator. In this paper we describe the environment that we have developed and present two examples of its use. The first example, procedure call instrumentation, illustrates a technique for gathering data on how certain architectural features are used. The second example, instruction tracing, illustrates a technique for collecting data that can then be used in trace—driven simulation.