Comparative evaluation of fuel consumption estimation models

Increased fossil fuel consumptions present a huge environmental challenge to the world. In order to meet the consumers' demands for transportation and at the same time to provide more fuel efficient vehicles, scientists are constantly searching for effective emissions and fuel consumption estimation models to protect the environment, especially to design more efficient control algorithms at traffic signalized intersections (e.g., eco-adaptive control) and promote environmentally friendly driving behaviors (e.g., eco-driving). The purpose of this research was to assess three existing fuel consumption estimation models using actual fuel consumption rates based on field measurements. The three models are the Virginia Tech Microscopic Energy and Emissions Model (VT-Micro), the Comprehensive Modal Emission Model (CMEM) and the Motor Vehicle Emission Simulator (MOVES) Model, and the field measured fuel consumptions are from instantaneous light duty vehicle (LDV) fuel consumption (FC) rate data collected by the Daegu Gyeongbuk Institute of Science and Technology of Korea (DGIST). Both the VT-Micro and the CMEM explained DGIST data reasonably well. All three models adequately tracked DGIST total fuel consumption over a fixed time interval

The Jefferson Lab High Resolution TDC Module

We discuss the design of a high resolution TDC module for use in nuclear physics experiments at Jefferson Lab. Preliminary results on the performance of the prototype module are presented

CODA performance in the real world

The most ambitious implementation of the Jefferson Lab data acquisition system (CODA) to date is for the CLAS spectrometer in Experimental Hall B. CLAS has over 40,000 instrumented channels and uses up to 30 front-end (FASTBUS/VME) crates in the DAQ subsystem. During the initial experiments the authors found that performance of the fully instrumented DAQ system did not scale as expected based on single point to point benchmarks. Over the past year the authors have been able to study various performance bottlenecks in the CLAS DAQ system including front-end real time performance, switched 100BaseT Ethernet data transport, and online data distribution and recording. Performance tuning was necessary for components on both real time (VxWorks) and UNIX (Solaris) operating systems. In addition, a new efficient Event Transfer System (ET) was developed to provide faster online monitoring while having minimal impact on data throughput to storage. They discuss these issues and efforts to overcome the real world problems associated with running a high performance DAQ system on a variety of commercial hardware and software

The Jefferson Lab Trigger Supervisor System

The authors discuss the design and performance of a Trigger Supervisor System for use in nuclear physics experiments at Jefferson Lab. They also discuss the enhanced features of a new Trigger Supervisor Module now under construction