A GPU-Based Integrated Simulation Framework for Modelling of Complex Subsurface Applications

2021 ◽  
Author(s):  
Mark Khait ◽  
Denis Voskov
Keyword(s):  
Practical Interest ◽  
Linear Interpolation ◽  
Memory Bandwidth ◽  
Complex Data ◽  
Simulation Framework ◽  
Integrated Simulation ◽  
Simulation Performance ◽  
Computational Performance ◽  
System Solution ◽  
System Memory

Abstract Alternative to CPU computing architectures, such as GPU, continue to evolve increasing the gap in peak memory bandwidth achievable on a conventional workstation or laptop. Such architectures are attractive for reservoir simulation, which performance is generally bounded by system memory bandwidth. However, to harvest the benefit of a new architecture, the source code has to be inevitably rewritten, sometimes almost completely. One of the biggest challenges here is to refactor the Jacobian assembly which typically involves large volumes of code and complex data processing. We demonstrate an effective and general way to simplify the linearization stage extracting complex physics-related computations from the main simulation loop and leaving only an algebraic multi-linear interpolation kernel instead. In this work, we provide the detailed description of simulation performance benefits from execution of the entire nonlinear loop on the GPU platform. We evaluate the computational performance of Delft Advanced Research Terra Simulator (DARTS) for various subsurface applications of practical interest on both CPU and GPU platforms, comparing particular workflow phases including Jacobian assembly and linear system solution with both stages of the Constraint Pressure Residual preconditioner.

Empirical Performance Analysis of HPC Benchmarks Across Variations in Cloud Computing

2013 ◽  
Vol 3 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Sindhu Mani
Keyword(s):  
Data Storage ◽  
High Performance ◽  
Large Data ◽  
Extensive Study ◽  
Memory Bandwidth ◽  
Platform As A Service ◽  
Data Intensive ◽  
Computational Performance ◽  
Empirical Performance ◽  
Data Intensive Applications

High Performance Computing (HPC) applications are scientific applications that require significant CPU capabilities. They are also data-intensive applications requiring large data storage. While many researchers have examined the performance of Amazon’s EC2 platform across some HPC benchmarks, an extensive study and their comparison between Amazon’s EC2 and Microsoft’s Windows Azure is largely missing with metrics such as memory bandwidth, I/O performance, and communication and computational performance. The purpose of this paper is to implement existing benchmarks to evaluate and analyze these metrics for EC2 and Windows Azure that span both Infrastructure-as-a-Service and Platform-as-a-Service types. This was accomplished by running MPI versions of STREAM, Interleaved or Random (IOR) and NAS Parallel (NPB) benchmarks on small and medium instance types. In addition a new EC2 medium instance type (m1.medium) was also included in the analysis. These benchmarks measure the memory bandwidth, I/O performance, communication and computational performance.

scholarly journals Integrated Simulation Framework for Assessing Turbocharger Fault Effects on Diesel-Engine Performance and Operability

2020 ◽  
Vol 146 (4) ◽  
pp. 04020023 ◽  
Author(s):  
Konstantinos Ntonas ◽  
Nikolaos Aretakis ◽  
Ioannis Roumeliotis ◽  
Efthimios Pariotis ◽  
Yiannis Paraskevopoulos ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Engine Performance ◽  
Simulation Framework ◽  
Integrated Simulation

scholarly journals Integrated method of analysis, visualization, and hardware for ship motion simulation

2017 ◽  
Vol 5 (3) ◽  
pp. 285-298 ◽  
Author(s):  
Seung-Ho Ham ◽  
Myung-Il Roh ◽  
Luman Zhao
Keyword(s):  
Motion Analysis ◽  
Ocean Waves ◽  
Ship Motion ◽  
Motion Simulation ◽  
Simulation Framework ◽  
Motion Platform ◽  
Integrated Simulation ◽  
Integrated Method ◽  
Real Objects ◽  
Simulation Time

Abstract Traditionally, graphs were the only way to show the results of ship motion analyses. They did not usually impose any feeling about how fast the ship could move or how large the positions of the ship changed. Currently, integrated simulations combining physics-based analyses with IT technologies, such as virtual reality (VR), motion platforms, or other hardware, can offer a potential solution. In ship motion analyses, the dynamic ship response can be obtained by considering the environmental loads, such as ocean waves, and VR technology can be used to visualize the analysis results in the virtual world. We can see the ship motion relative to textures of real objects, including the water and sky, as if in the real world. The results calculated from the ship motion analysis can also be transferred to the motion platform to generate realistic movements. However, it is not easy to integrate three different technologies in one system because they have different purposes and have been developed individually. To solve this problem, an integrated simulation framework based on three different technologies is proposed. The proposed framework can be used to synchronize the simulation time and exchange the data through the middleware using a standardized data structure. Furthermore, we can easily add new components or remove the existing components in the simulation. To verify the efficiency and applicability of the proposed framework, the motion simulation of a drillship is applied. Highlights We propose an integrated simulation framework for analysis, visualization, and hardware. Multibody dynamics is used for the motion analysis. We perform the integrated motion simulation of a drillship. The motion analysis, visualization, and motion platform of a drillship are perfectly synchronized.

Modeling uncertainty with an integrated simulation system

2005 ◽  
Vol 32 (3) ◽  
pp. 533-542 ◽  
Author(s):  
Lingguang Song ◽  
Hussien T Al-Battaineh ◽  
Simaan M AbouRizk
Keyword(s):  
Traditional Approach ◽  
Project Performance ◽  
Working Environment ◽  
Ann Model ◽  
Simulation Framework ◽  
Integrated Simulation ◽  
Activity Duration ◽  
Steel Fabrication ◽  
Artificial Neural Network Ann ◽  
Physical Features

Uncertainty inevitably affects the performance of a construction project. The ability to identify uncertainty and quantitatively evaluate its impact on the project performance can significantly enhance the accuracy and reliability of a project plan. This paper describes a methodology to classify, model, and reduce uncertainty. This method was implemented within an integrated simulation framework capable of capturing physical features of the facility to be constructed, uncertainty in the working environment, and the construction processes. A "virtual" steel fabrication shop model was developed using the proposed framework to model uncertainty in a steel fabrication shop environment. The artificial neural network (ANN) modeling technique, which plays a significant role in the simulation model, was used to model activity duration based on the identified productivity influencing factors and data collected through a time study project conducted in the fabrication shop. The virtual shop model with the embedded ANN model proved to be more accurate than the traditional approach of modeling activity duration using statistical distributions.Key words: uncertainty, classification, modeling, simulation, neural networks.

scholarly journals Integrated Systems Simulation for Assessing Fuel Thermal Management Capabilities for Hybrid-Electric Rotorcraft

2020 ◽  
Author(s):  
Ioannis Roumeliotis ◽  
Lorenzo Castro ◽  
Soheil Jafari ◽  
Vassilios Pachidis ◽  
Louis De Riberolles ◽  
...  
Keyword(s):  
Thermal Management ◽  
Electric Propulsion ◽  
Cooling Capacity ◽  
Propulsion System ◽  
Fuel Tank ◽  
Thermal Loads ◽  
Simulation Framework ◽  
Propulsion Systems ◽  
Integrated Simulation ◽  
Hybrid Electric

Abstract Future aircraft and rotorcraft propulsion systems should be able to meet ambitious targets and severe limitations set by governments and organizations. These targets cannot be achieved through marginal improvements in turbine technology or vehicle design. Hybrid-electric propulsion is being widely considered as a revolutionary concept to further improve the environmental impact of air travel. One of the most important challenges and barriers in the development phase of hybrid-electric propulsion systems is the Thermal Management System (TMS) design, sizing and optimization for addressing the increased thermal loads due to the electric power train. The aim of this paper is to establish an integrated simulation framework including the vehicle, the propulsion system and the fuel-oil system (FOS) for assessing the cooling capability of the FOS for the more electric era of rotorcrafts. The framework consists of a helicopter model, propulsion system models, both conventional and hybrid-electric, and a FOS model. The test case is a twin-engine medium (TEM) helicopter flying a representative Passenger Air Transport (PAT) mission. The conventional power plant heat loads are calculated and the cooling capacity of the FOS is quantified for different operating conditions. Having established the baseline, three different Power Management Strategies (PMS) are considered and the integrated simulation framework is utilized for evaluating FOS temperatures. The results highlight the limitations of existing rotorcraft FOS to cope with the high values of thermal loads associated with hybridization for the cases examined. Hence, new ideas and embodiments should be identified and assessed. The case of exploiting the fuel tank as a heat sink is investigated and the results indicate that recirculating fuel to the fuel tank can enhance the cooling capacity of conventional FOS.

scholarly journals Process Simulation Framework Design and Validation with Grinding Systems

2019 ◽  
Vol 9 (1) ◽  
pp. 2861-2869
Keyword(s):  
Process Simulation ◽  
Simulation Software ◽  
Software Systems ◽  
Simulation Framework ◽  
Simulation Accuracy ◽  
Simulation Performance ◽  
Control Optimization ◽  
Framework Design ◽  
Knowledge Rules ◽  
Intelligent Model

Process Industrial & their complex control operations require comprehensive simulation software systems for modeling plant dynamics and analyzing gaps and to achieve optimal control efficiency. These models support in training plant engineers on various process scenarios in controlled pseudo real time environment. Higher degree of model designing customization, flexibility, scalability, cost efficiency and domain agnostic solution features, are the desired characteristics of any process simulation framework. This paper formulates prototype design of an integrated generic process simulator platform and its components, enabling intuitive and interactive representation of intelligent model formats, facts, knowledge, rules & behaviors. The benefits range from safer process training, analysis / synthesis of controller models; control optimization and theoretical learning. The simulation performance of proposed framework is verified through material fineness control modeling of rotary vertical grinding mill. The adaptive leaning features, with hybrid prediction model validations results in the simulation accuracy and results are compared with prevalent systems.

scholarly journals Numerical investigation of the Carleman system

Vestnik MGSU ◽  
2015 ◽  
pp. 7-15
Author(s):  
Ol’ga Aleksandrovna Vasil’eva
Keyword(s):  
Cauchy Problem ◽  
Equilibrium State ◽  
Numerical Investigation ◽  
Initial Conditions ◽  
Practical Interest ◽  
Statistical Characteristics ◽  
Stabilization Time ◽  
System Solution ◽  
Stochastic Solution ◽  
The Cauchy Problem

In the article the Cauchy problem of the Carleman equation is considered. The Carleman system of equations is a model problem of the kinetic theory of gases. It is a discrete kinetic model of one-dimensional gas consisting of identical monatomic molecules. The molecules can have one of two speeds, which have equal values and opposite directions. This system of the equations is quasi-linear hyperbolic system of partial differential equations. There is no analytic solution for this problem in general case. So, the numerical investigation of the Cauchy problem of the Carleman system solution is very important.The paper presents and discusses the results of the numerical investigation of the Cauchy problem for the studied system solution with periodic initial conditions. The dependence of the stabilization time of the solution and the time dependence of energy exchange from small parameter are obtained.The second point of the paper is numerical investigation of the solution of the Cauchy problem with non-periodic initial conditions. The solution stabilization to the equilibrium state is obtained. The solution stabilization time is compared with stabilization time in periodic case.The final point of the paper is numerical investigation of the Cauchy problem with stationary normal processes as initial conditions. The solution to this problem is two stationary stochastic processes for any fixed value of time variable. As a rule, the practical interest is not a stochastic solution but its statistical characteristics. The stochastic solution realization is presented and discussed. The dependence of the mathematical expectation of the solution deviation modulus from equilibrium state is obtained. It demonstrates the process of the solution stabilization.

scholarly journals Proposal for Medical Data Transmission in Healthcare Systems

2020 ◽  
Vol 4 (3) ◽  
pp. 580-580
Author(s):  
Reinaldo Padilha França
Keyword(s):  
Positive Impact ◽  
Signal Transmission ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Background Information ◽  
Generation Process ◽  
Discrete Events ◽  
Computational Performance ◽  
System Memory ◽  
Waiting Periods

Background: Information systems used in hospitals are slow and consume a lot of system memory, facilitating crashes, impacting patients seeking consultation face long waiting periods by a medical specialist; Still considering that exchange patient data and medical consultations in system interconnected between hospitals, for scheduling of consultations may become even more latent.Methods: Aiming to solve such problems, the present study implements modeling with discrete-event technology applied to a healthcare system, modulating the signal transmitted with the DQPSK format, through the simulation environment, the Simulink of the MATLAB software, improving the transmission of data, through a pre-coding process of bits adopting discrete events in the signal before modulation.Results: This study aims to increase the information capacity for healthcare systems, bringing a new approach for signal transmission, undertaken in the discrete domain employing the discrete entities in the bit generation process, this use being the differential applied on the bit itself, in the physical layer, showing better computational performance regarding memory utilization related to compression of information, showing an improvement of 101.52%.Conclusion: The proposal developed has the properties of improving the capacity of hospital services and can increase the performance of the communication between all medical devices, this positive impact is the result that the data stream will consume fewer communication resources.

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