Brake System Component Characterization for System Response Performance: A System Level Test Method and Associated Theoretical Correlation

2004 ◽  
Author(s):  
Patrick Tinchi Pang ◽  
David Agnew
Keyword(s):  
Test Method ◽  
System Level ◽  
Brake System ◽  
System Component ◽  
System Response ◽  
Response Performance

Modeling the System and Component Performance Interactions of a SOFC Based APU for Changes in Application Load: Transient Response and Control Strategy

2004 ◽  
Author(s):  
D. F. Rancruel ◽  
M. R. von Spakovsky
Keyword(s):  
Transient Response ◽  
Control Strategy ◽  
Control Strategies ◽  
Control Variable ◽  
System Level ◽  
System Component ◽  
System Response ◽  
Optimal Control Strategy ◽  
Synthesis Design ◽  
And Control

Solid-Oxide-Fuel-Cell (SOFC) stacks respond in seconds to changes in load while the balance of plant subsystem (BOPS) responds in times several orders of magnitude higher. This dichotomy diminishes the reliability and performance of SOFC electrodes with changes in load. In the same manner current and voltage ripples which result from particular power electronic subsystem (PES) topologies and operation produce a negative effect on the SOFC stack subsystem (SS) performance. The difference in transient response among the sub-systems must be approached in a way which makes operation of the entire system not only feasible but ensures that efficiency and power density, fuel utilization, fuel conversion, and system response are optimal at all load conditions. Thus, a need exists for the development of transient component- and system-level models of SOFC based auxiliary power units (APUs), i.e. coupled BOPS, SS, and PES, and the development of methodologies for optimizing subsystem responses and for investigating system-interaction issues. In fact the transient process occurring in a SOFC based APU should be systematically treated during the entire creative process of synthesis, design, and operational control, leading in its most general sense to a dynamic optimization problem. This entails finding an optimal system/component synthesis/design, taking into account on- and off-design operation, which in turn entails finding an optimal control strategy and control profile for each sub-system/component and control variable. Such an optimization minimizes an appropriate objective function while satisfying all system constraints. A preliminary set of chemical, thermal, electrochemical, electrical, and mechanical models based on first principles and validated with experimental data have been developed and implemented using a number of different platforms. These models have been integrated in order to be able to perform component, subsystem, and system analyses as well as develop optimal syntheses/designs and control strategies for transportation and stationary SOFC based APUs. Some pertinent results of these efforts are presented here.

Dynamic Infrared System Level Fault Isolation

2003 ◽  
Author(s):  
John A. Naoum ◽  
Johan Rahardjo ◽  
Yitages Taffese ◽  
Marie Chagny ◽  
Jeff Birdsley ◽  
...  
Keyword(s):  
Fault Isolation ◽  
System Level ◽  
System Component ◽  
Component Level ◽  
Ir Imaging ◽  
Non Destructive

Abstract The use of Dynamic Infrared (IR) Imaging is presented as a novel, valuable and non-destructive approach for the analysis and isolation of failures at a system/component level.

scholarly journals Machine Learning and Cryptographic Algorithms – Analysis and Design in Ransomware and Vulnerabilities Detection

2020 ◽  
Author(s):  
Nandkumar Niture
Keyword(s):  
Machine Learning ◽  
Intelligent System ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
System Level ◽  
Management Systems ◽  
System Response ◽  
Hard Part ◽  
Analysis And Design ◽  
Password Management

The AI, deep learning and machine learning algorithms are gaining the ground in every application domain of information technology including information security. In formation security domain knows for traditional password management systems, auto-provisioning systems and user information management systems. There is another raising concern on the application and system level security with ransomware. On the existing systems cyber-attacks of Ransomware asking for ransom increasing every day. Ransomware is the class of malware where the goal is to gain the data through encryption mechanism and render back with the ransom. The ransomware attacks are mainly on the vulnerable systems which are exposed to the network with weak security measures. With the help of machine learning algorithms, the pattern of the attacks can be analyzed. Create or discuss a workaround solution of a machine learning model with combination of cryptographic algorithm which will enhance the effectiveness of the system response to the possible attacks. The other part of the problem, which is hard part to create an intelligence for the organizations for preventing the ransomware attacks with the help of intelligent system password management and intelligent account provisioning. In this paper I elaborate on the machine learning algorithms analysis for the intelligent ransomware detection problem, later part of this paper would be design of the algorithm.

Hierarchical Control Co-Design Using a Model Fidelity-Based Decomposition Framework

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Austin L. Nash ◽  
Neera Jain
Keyword(s):  
Hierarchical Control ◽  
Coupled Systems ◽  
System Level ◽  
Design Stage ◽  
System Component ◽  
Model Parameters ◽  
Level Control ◽  
Efficient Manner ◽  
Model Fidelity ◽  
Time Operation

Abstract Increasing performance demands and constraints are necessitating the design of highly complex, integrated systems across multiple sectors, including transportation and energy. However, conventional design approaches for such systems are largely siloed and focused on steady-state operation. To accommodate tightening operating envelopes, new design paradigms are needed that explicitly consider system-component interactions and their implications on transient performance at the system design stage. In this work, we present a model fidelity-based decomposition (MFBD) hierarchical control co-design (HCCD) algorithm designed to optimize system performance characteristics, with an emphasis on robustness to transient disturbances during real-time operation. Our framework integrates system level control co-design (CCD) with high-fidelity component design optimization in a computationally efficient manner for classes of highly coupled systems in which the coupling between subproblems cannot be fully captured using existing analytical relationships. Our algorithm permits scalable decomposition of computationally intensive component models and addresses coupling issues between subproblems in part by introducing an intermediate optimization procedure to solve for reduced-order model parameters that maximize the accuracy of the lumped-parameter control model required in the CCD algorithm. We demonstrate the merits of the MFBD HCCD algorithm, in comparison to an all-at-once (AAO) CCD approach, through a case study on aircraft dynamic thermal management. Our results show that our decomposition-based solution matches the AAO optimal cost to within 2.5% with a 54% reduction in computation time.

Shock and Vibration Survivability Prediction Using Failure Envelopes for Electronic and MEMS Packaging

2005 ◽  
Author(s):  
Pradeep Lall ◽  
Dhananjay Panchagade ◽  
Prakriti Choudhary ◽  
Jeff Suhling ◽  
Sameep Gupte
Keyword(s):  
Electronic Packaging ◽  
Wavelet Transforms ◽  
High Speed ◽  
Damage Index ◽  
Test Method ◽  
System Level ◽  
Failure Envelope ◽  
Ball Grid Arrays ◽  
Cost Constraints ◽  
Damage Progression

Product level assessment of drop and shock reliability relies heavily on experimental test methods. Prediction of drop and shock survivability is largely beyond the state-of-art. However, the use of experimental approach to test out every possible design variation, and identify the one that gives the maximum design margin is often not feasible because of product development cycle time and cost constraints. Presently, one of the primary methodologies for evaluating shock and vibration survivability of electronic packaging is the JEDEC drop test method, JESD22-B111 which tests board-level reliability of packaging. However, packages in electronic products may be subjected to a wide-array of boundary conditions beyond those targeted in the test method. In this paper, a failure-envelope approach based on wavelet transforms and damage proxies has been developed to model drop and shock survivability of electronic packaging. Data on damage progression under transient-shock and vibration in both 95.5Sn4.0Ag0.5Cu and 63Sn37Pb ball-grid arrays has been presented. Component types examined include — flex-substrate and rigid substrate ball-grid arrays. Dynamic measurements like acceleration, strain and resistance are measured and analyzed using high-speed data acquisition system capable of capturing in-situ strain, continuity and acceleration data in excess of 5 million samples per second. Ultra high-speed video at 150,000 fps per second has been used to capture the deformation kinematics. The concept of relative damage index has been used to both evaluate and predict damage progression during transient shock. The failure-envelope provides a fundamental basis for development of component integration guidelines to ensure survivability in shock and vibration environments at a user-specified confidence level. The approach is scalable to application at system-level. Explicit finite-element models have been developed for prediction of shock survivability based on the failure envelope. Model predictions have been correlated with experimental data for both leaded and leadfree ball-grid arrays.

Low-Pressure System Component Advancements and Its Influence on Future Turbofan Engine Emissions

2009 ◽  
Author(s):  
Tomas Gro¨nstedt ◽  
Dax Au ◽  
Konstantinos Kyprianidis ◽  
Stephen Ogaji
Keyword(s):  
Power Plants ◽  
Assessment Tool ◽  
Low Pressure ◽  
System Level ◽  
Research Progress ◽  
System Component ◽  
Engine Fuel ◽  
Pressure System ◽  
Low Pressure System ◽  
The Impact

Within the European research project EnVIronmenTALly Friendly Aero Engines, VITAL, a number of low pressure system component technologies are being investigated. The emerging progress will allow the design of new power plants providing a step change in engine fuel burn and noise. As part of the VITAL project a Technoeconomic and Environmental Risk Assessment tool, the TERA2020, is being developed. Within this tool, means to assess the impact of component technology progress on the engine/aircraft system level has been implemented. Sensitivities relating parameters traditionally used to describe component performance, such as allowable shaft torque, low pressure turbine stage loading, fan blade weight and system level parameters have been established. This allows a direct assessment of the impact of component research progress on the VITAL power plant CO2 and noise emissions.

scholarly journals Machine Learning and Cryptographic Algorithms – Analysis and Design in Ransomware and Vulnerabilities Detection

2020 ◽  
Author(s):  
Nandkumar Niture
Keyword(s):  
Machine Learning ◽  
Intelligent System ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
System Level ◽  
Management Systems ◽  
System Response ◽  
Hard Part ◽  
Analysis And Design ◽  
Password Management

The AI, deep learning and machine learning algorithms are gaining the ground in every application domain of information technology including information security. In formation security domain knows for traditional password management systems, auto-provisioning systems and user information management systems. There is another raising concern on the application and system level security with ransomware. On the existing systems cyber-attacks of Ransomware asking for ransom increasing every day. Ransomware is the class of malware where the goal is to gain the data through encryption mechanism and render back with the ransom. The ransomware attacks are mainly on the vulnerable systems which are exposed to the network with weak security measures. With the help of machine learning algorithms, the pattern of the attacks can be analyzed. Create or discuss a workaround solution of a machine learning model with combination of cryptographic algorithm which will enhance the effectiveness of the system response to the possible attacks. The other part of the problem, which is hard part to create an intelligence for the organizations for preventing the ransomware attacks with the help of intelligent system password management and intelligent account provisioning. In this paper I elaborate on the machine learning algorithms analysis for the intelligent ransomware detection problem, later part of this paper would be design of the algorithm.

Sign in / Sign up

Export Citation Format

Share Document