Browse Topic: Mathematical models
ABSTRACT This document describes how to maximize the human potential/capital of your system or business by developing a Corporate Awareness. It explains and defines how Leadership, Leadership Process and human potential interrelate. It next focuses on the relation between Leadership Process and corporate culture, giving suggestions on how to develop a Corporate Self Awareness, leading to the ability to control corporate culture, in a manner that maximizes the human potential of the system/business. Next there is a discussion of solutions based on mathematical formulas and algorithms that can be implemented to define and measure Leadership Process using modern free source IT tools. Finally, this paper will provide support for aligning system/business mission/products with the Leadership Process so that Leadership maximizes the system/business human potential. It will suggest that modern IT tools be implemented as part of the solution and provide the concept of BWIKI as a solution
ABSTRACT As contracts move from cost plus to fixed deliverables, total project cost and reducing schedules become more important. This paper will show how Model Driven Development can address common challenges in the system design, verification & testing of complex systems and systems of systems. Project success requires that hardware, software, and test teams fluently integrate application software, controlling firmware, analog and digital hardware, and mechanical components, which often proves to be costly in terms of time, money, and engineering resources. Model Driven Development and virtual prototyping using a tools flow emphasizing requirements tracing, UML / SysML system modeling, and linking to functional FPGA, IC, PCB and cabling domains supports system engineering teams along with software, digital hardware, analog hardware, system interconnect algorithm development, hardware / software co-simulation, and virtual system integration. This paper covers such solutions that
ABSTRACT This presentation will review the ongoing lessons learned from a joint Industry/DoD collaborative program to explore this area over the past 5 years. The discussion will review the effectiveness of integrating multiple new technologies (combined with select COTS elements) to provide a complete solution designed to reduce spares stockpiles, maximize available manpower, reduce maintenance downtime and reduce vehicle lifecycle costs. A number of new and emerging technology case studies involving diagnostic sensors (such as battery health monitors), knowledge management data accessibility, remote support-based Telematics, secure communication, condition-based software algorithms, browser-based user interfaces and web portal data delivery will be presented
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To understand effect of thermal hazards of LIBs during TR event, it is important to study flame propagation behaviour of LIBs during storage and transport applications. The process of flame propagation involves complex phenomena of gas phase behavior of LIBs. Present paper attempts a numerical investigation to portray this complex phenomenon. This paper investigates 18650 lithium cell considering two different chemistries NMC and LFP. A 3D numerical CFD model has been constructed to predict the gas phase behavior, threshold internal pressure, and cell gas venting of an 18650-lithium cell under thermal runaway conditions. The gas phase processes are modelled using the 4-equation thermal abuse model, while the cell's venting mechanism is modelled using Darcy's equation. Present work is divided into two parts: 1) Venting gas Internal pressure prediction 2) modeling thermal runaway event. Both procedures are implemented on two different cell chemistries to understand and evaluate following
Autonomous vehicle navigation requires signal processing of the vehicle’s sensors to provide meaningful information to the planners such that challenging artifacts like shadows, rare events, obstructive vegetation, etc. are identified properly, avoiding ill-informed navigation. Using a single algorithm such as semantic segmentation of camera images is often not enough to identify those challenging features but can be overcome by processing more than one type of sensor and fusing their results. In this work, semantic segmentation of camera image and LiDAR point cloud signals is performed using Echo State Networks to overcome the challenge of shadows identified as obstructions in off-road terrains. The coordination of algorithms processing multiple sensor signals is shown to avoid unnecessary road obstructions caused by high-contrast shadows for more informed navigational planning
Resupply missions are critical logistical parts of modern warfare. Supply vehicles carrying fuel and ammunition are high-value targets meaning that the route chosen to approach such a mission is sensitive to risk and a critical time of delivery. We address the problem of a supply vehicle that needs to find a secure path to link up with a mobile frontline unit that has a fixed known itinerary. This paper presents a resupply path planning algorithm, the Adaptive Intercepting Path Planning (AIPP) algorithm, that balances risk and travel time to find the most suitable rendezvous point among several. The algorithm generates the least risky route that meets the rendezvous deadline
To expand the availability of electricity generated from nuclear power, several countries have started developing designs for small modular reactors (SMRs), which could take less time and money to construct compared to existing reactors
This article offers an algorithmic solution for moving a homogeneous platoon of position-controlled vehicles on a curved path with varying speeds and in the presence of communication losses and delays. This article considers a trajectory-based platooning with the leader–following communication topology, where the lead vehicle communicates its reference position and orientation to each autonomous follower vehicle. A follower vehicle stores this communicated information for a specific period as a virtual trail of the lead vehicle starting from the lead vehicle’s initial position and orientation. An algorithm uses this trail to find the follower vehicle’s reference position and orientation on that trail, such that the follower vehicle maintains a constant distance from the lead vehicle. The proposed algorithm helps form a platoon where each vehicle can traverse a curve with varying speeds. In contrast, in the existing literature, most of the solutions for vehicle platooning on a curved
In the context of urban smart mobility, vehicles have to communicate with each other, surrounding infrastructure, and other traffic participants. By using Vehicle2X communication, it is possible to exchange the vehicles’ position, driving dynamics data, or driving intention. This concept yields the use for cooperative driving in urban environments. Based on current V2X-communication standards, a methodology for cooperative driving of automated vehicles in mixed traffic scenarios is presented. Initially, all communication participants communicate their dynamic data and planned trajectory, based on which a prioritization is calculated. Therefore, a decentralized cooperation algorithm is introduced. The approach of this algorithm is that every traffic scenario is translatable to a directed graph, based in which a solution for the cooperation problem is computed via an optimization algorithm. This solution is either computed decentralized by various traffic participants, who share and
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