scholarly journals European traffic on road bridges and recalibration of damage equivalence factor for fatigue verification

ce/papers ◽  
2021 ◽  
Vol 4 (2-4) ◽  
pp. 1065-1075
Author(s):  
Gianluca Bianchi ◽  
Alain Nussbaumer ◽  
José J. Oliveira Pedro
Keyword(s):  
Equivalence Factor

scholarly journals The Acute Toxicity of Tetrodotoxin and Tetrodotoxin–Saxitoxin Mixtures to Mice by Various Routes of Administration

Toxins ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 423 ◽  
Author(s):  
Sarah Finch ◽  
Michael Boundy ◽  
D. Harwood
Keyword(s):  
One Health ◽  
Acute Oral Toxicity ◽  
Bivalve Molluscs ◽  
Oral Toxicity ◽  
Routes Of Administration ◽  
Paralytic Shellfish ◽  
Guideline Value ◽  
Equivalence Factor ◽  
Scientific Opinion ◽  
Additive Toxicity

Tetrodotoxin (TTX) is a potent neurotoxin associated with human poisonings through the consumption of pufferfish. More recently, TTX has been identified in bivalve molluscs from diverse geographical environments, including Europe, and is therefore recognised as an emerging threat to food safety. A recent scientific opinion of the EFSA Panel on Contaminants in the Food Chain recognised the need for further data on the acute oral toxicity of TTX and suggested that, since saxitoxin (STX) and TTX had similar modes of action, it was possible that their toxicities were additive so could perhaps be combined to yield one health-based guideline value. The present study determined the toxicity of TTX by various routes of administration. The testing of three different mixtures of STX and TTX and comparing the experimentally determined values to those predicted on the basis of additive toxicity demonstrated that the toxicities of STX and TTX are additive. This illustrates that it is appropriate to treat TTX as a member of the paralytic shellfish group of toxins. Since the toxicity of TTX was found to be the same as STX by feeding, a molar toxicity equivalence factor of 1.0 for TTX can be applied.

Dynamic Programming-Informed Equivalent Cost Minimization Control Strategies for Hybrid-Electric Vehicles

2013 ◽  
Vol 135 (5) ◽  
Author(s):  
Dekun Pei ◽  
Michael J. Leamy
Keyword(s):  
Dynamic Programming ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Cost Minimization ◽  
Global Optimum ◽  
Robust Controller ◽  
Drive Cycle ◽  
Suggested Approach ◽  
Equivalence Factor ◽  
Hybrid Electric

This paper presents a direct mathematical approach for determining the state of charge (SOC)-dependent equivalent cost factor in hybrid-electric vehicle (HEV) supervisory control problems using globally optimal dynamic programming (DP). It therefore provides a rational basis for designing equivalent cost minimization strategies (ECMS) which achieve near optimal fuel economy (FE). The suggested approach makes use of the Pareto optimality criterion that exists in both ECMS and DP, and as such predicts the optimal equivalence factor for a drive cycle using DP marginal cost. The equivalence factor is then further modified with corrections based on battery SOC, with the aim of making the equivalence factor robust to drive cycle variations. Adaptive logic is also implemented to ensure battery charge sustaining operation at the desired SOC. Simulations performed on parallel and power-split HEV architectures demonstrate the cross-platform applicability of the DP-informed ECMS approach. Fuel economy data resulting from the simulations demonstrate that the robust controller consistently achieves FE within 1% of the global optimum prescribed by DP. Additionally, even when the equivalence factor deviates substantially from the optimal value for a drive cycle, the robust controller can still produce FE within 1–2% of the global optimum. This compares favorably with a traditional ECMS controller based on a constant equivalence factor, which can produce FE 20–30% less than the global optimum under the same conditions. As such, the controller approach detailed should result in ECMS supervisory controllers that can achieve near optimal FE performance, even if component parameters vary from assumed values (e.g., due to manufacturing variation, environmental effects or aging), or actual driving conditions deviate largely from standard drive cycles.

Adaptive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles

2010 ◽  
Author(s):  
Simona Onori ◽  
Lorenzo Serrao ◽  
Giorgio Rizzoni
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Optimal Solution ◽  
State Of Charge ◽  
Management Problem ◽  
Equivalence Factor ◽  
Hybrid Electric ◽  
Equivalent Consumption Minimization Strategy ◽  
Adaptation Law

This paper proposes a new method for solving the energy management problem for hybrid electric vehicles (HEVs) based on the equivalent consumption minimization strategy (ECMS). After discussing the main features of ECMS, an adaptation law of the equivalence factor used by ECMS is presented, which, using feedback of state of charge, ensures optimality of the strategy proposed. The performance of the A-ECMS is shown in simulation and compared to the optimal solution obtained with dynamic programming.

scholarly journals Carcinogenic Potency of Airborne Polycyclic Aromatic Hydrocarbons in Relation to the Particle Fraction Size

2018 ◽  
Vol 15 (11) ◽  
pp. 2485 ◽  
Author(s):  
Gordana Pehnec ◽  
Ivana Jakovljević
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Road Traffic ◽  
Particle Fraction ◽  
Carcinogenic Potency ◽  
Equivalence Factor ◽  
Polycyclic Aromatic ◽  
Individual Pahs ◽  
The Individual ◽  
Mass Concentrations

Polycyclic aromatic hydrocarbons (PAHs) that are bound to particulate matter can have adverse effects on human health. Particle size plays an important role in assessing health risks. The aim of this study was to compare concentrations of PAHs bound to particle fractions PM10, PM2.5, and PM1, as well as to estimate their carcinogenic potency and relative contributions of the individual PAHs to the carcinogenic potency in relation to the size of the particle. Measurements of ten PAHs were carried out in 2014 at an urban location in the northern part of Zagreb, Croatia. 24-h samples of the PM10, PM2.5, and PM1 particle fraction were collected over forty days per season. Carcinogenic potency of PAHs was estimated by calculating benzo(a)pyrene equivalent concentrations while using three different toxic equivalence factor (TEF) schemes. The total carcinogenic potency (TCP) and percentage contributions differed significantly depending on the TEF scheme used. The lowest PAH mass concentrations and TCPs were in summer and the highest in winter. The contributions of individual PAHs to the sum of PAH mass concentrations remained similar in all fractions and seasons, while in fractions PM10–2.5 and PM2.5–1 they varied significantly. Road traffic represented the important source of PAHs in all fractions and throughout all seasons. Other sources (wood and biomass burning, petroleum combustion) were also present, especially during winter as a consequence of household heating. The highest contribution to the TCP came from benzo(a)pyrene, dibenzo(ah)antrachene, indeno(1,2,3,cd)pyrene, and benzo(b)fluoranthene (together between 87% and 96%) in all fractions and seasons. In all cases, BaP showed the highest contribution to the TCP regardless relatively low contributions to the mass of total PAHs and it can be considered as a good representative for assessing the carcinogenicity of the PAH mixture. When comparing the TCP of PAHs in PM10 and PM2.5 fractions, it was found that about 21–26% of carcinogenic potency of the PAH mixture belonged to the PM2.5 fraction. Comparison of TCP in PM2.5 and PM1 showed that about 86% of carcinogenic potency belonged to the PM1 fraction, regardless of the TEF scheme used.

scholarly journals Robust proportional ECMS control of a parallel hybrid electric vehicle

2016 ◽  
Vol 231 (1) ◽  
pp. 99-119 ◽  
Author(s):  
Wisdom Enang ◽  
Chris Bannister
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Driving Cycle ◽  
State Of Charge ◽  
Fuel Savings ◽  
Equivalence Factor ◽  
Battery State Of Charge ◽  
Hybrid Electric

Improved fuel efficiency in hybrid electric vehicles requires a delicate balance between the internal combustion engine usage and battery energy, using a carefully designed energy management control algorithm. Numerous energy management strategies for hybrid electric vehicles have been proposed in literature, with many of these centered on the equivalent consumption minimisation strategy (ECMS) owing to its potential for online implementation. The key challenge with the equivalent consumption minimisation strategy lies in estimating or adapting the equivalence factor in real-time so that reasonable fuel savings are achieved without over-depleting the battery state of charge at the end of the defined driving cycle. To address the challenge, this paper proposes a novel state of charge feedback ECMS controller which simultaneously optimises and selects the adaption factors (proportional controller gain and initial equivalence factor) as single parameters which can be applied in real time, over any driving cycle. Unlike other existing state of charge feedback methods, this approach solves a conflicting multiple-objective optimisation control problem, thus ensuring that the obtained adaptation factors are optimised for robustness, charge sustenance and fuel reduction. The potential of the proposed approach was thoroughly explored over a number of legislative and real-world driving cycles with varying vehicle power requirements. The results showed that, whilst achieving fuel savings in the range of 8.40 −19.68% depending on the cycle, final battery state of charge can be optimally controlled to within ±5% of the target battery state of charge.

Time-Temperature Superposition and Physical Hardening Effects in Low-Temperature Asphalt Binder Grading

2003 ◽  
Vol 1829 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Arindam Basu ◽  
Mihai O. Marasteanu ◽  
Simon A. M. Hesp
Keyword(s):  
Low Temperature ◽  
Superposition Principle ◽  
Asphalt Binder ◽  
Test Results ◽  
Physical Hardening ◽  
Equivalence Factor ◽  
Temperature Superposition ◽  
Current Specification ◽  
Time Temperature Superposition ◽  
Time Temperature Superposition Principle

During the development of the Strategic Highway Research Program low-temperature binder specifications, in an effort to propose practical laboratory tests that require less time to perform, the time–temperature superposition principle was used to show that the stiffness after 2 h of loading at the performance-graded (PG) low temperature can be approximated by the stiffness after 60 s of loading at 10°C above the PG low temperature. This equivalence principle was developed on the basis of test results from the eight core asphalts and is widely accepted today. However, actual 2-h tests were not performed to experimentally validate this equivalence. Furthermore, the effect of physical hardening on time–temperature superposition was not considered. The validity of the time–temperature equivalence factor used in the low-temperature specification criterion and the ways in which the deviations could affect the current specification are evaluated.

scholarly journals Availability Equivalence Analysis of a Repairable Series-Parallel System

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Linmin Hu ◽  
Dequan Yue ◽  
Dongmei Zhao
Keyword(s):  
Parallel System ◽  
Failure Rates ◽  
Numerical Examples ◽  
Equivalence Factor ◽  
System Components ◽  
System Designs

This paper studies the availability equivalence of different designs of a repairable series-parallel system. Under the assumption that the system components have constant failure rates and repair rates, we derive the availability of the original and improved systems according to reduction, increase, hot duplication, warm duplication and cold duplication methods, respectively. The availability equivalence factor is introduced to compare different system designs. Two types of availability equivalence factors of the system are obtained. Numerical examples are provided to interpret how to utilize the obtained results.

Optimal Reliability Equivalence Factor for Reliability System Improvement Using Memetic Algorithm

2017 ◽  
Vol 24 (06) ◽  
pp. 1740008 ◽  
Author(s):  
Z. Ramezani ◽  
A. Pourdarvish ◽  
A. H. S. Garmabaki ◽  
P. K. Kapur
Keyword(s):  
System Reliability ◽  
Reduction Method ◽  
Memetic Algorithm ◽  
Redundancy Allocation Problem ◽  
Equivalence Factor ◽  
Reduction Methods ◽  
Space Limitation ◽  
System Improvement ◽  
Instance Space ◽  
Optimal Reduction

In this paper, optimal reduction and redundancy methods for reliability system improvement have been proposed. Multilevel redundancy allocation problem (MLRAP) based on hot and cold redundancies has been considered. For various reasons, for instance, space limitation, high cost and so on, redundancy method cannot always be applied to improve system reliability. Hence, the concept of equivalence has been presented to choose a more suitable method. In these conditions, optimal reduction method has been applied instead of optimal redundancy method, so that we decide what appropriate degree to decrease the failure rate is. To solve this problem, the value of optimal reliability equivalence factor is obtained by equating two obtained reliability functions based on optimal redundancy and reduction methods. Result shows that equivalence value maximizes the efficiency of the system performance in reduction method instead of redundancy method. Finally, the numerical examples illustrate the results obtained theoretically.

An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management Based on Driving Pattern Recognition

2006 ◽  
Author(s):  
Bo Gu ◽  
Giorgio Rizzoni
Keyword(s):  
Pattern Recognition ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Driving Pattern ◽  
Equivalence Factor ◽  
Equivalent Fuel ◽  
Driving Conditions ◽  
Equivalent Fuel Consumption

In this paper we present a novel adaptation method for the Adaptive Equivalent fuel Consumption Minimization Strategy (A-ECMS). The approach is based on Driving Pattern Recognition (DPR). The Equivalent (fuel) Consumption Minimization Strategy (ECMS) method provides real-time suboptimal energy management decisions by minimizing the "equivalent" fuel consumption of a hybrid-electric vehicle. The equivalent fuel consumption is a combination of the actual fuel consumption and electrical energy use, and an equivalence factor is used to convert electrical power used into an equivalent chemical fuel quantity. In this research, a driving pattern recognition method is used to obtain better estimation of the equivalence factor under different driving conditions. A time window of past driving conditions is analyzed periodically and recognized as one of the Representative Driving Patterns (RDPs). Periodically updating the control parameter according to the driving conditions yields more precise estimation of the equivalent fuel consumption cost, thus providing better fuel economy. Besides minimizing the instantaneous equivalent fuel consumption, the battery State of Charge (SOC) management is also maintained by using a PI controller to keep the SOC around a nominal value. The primary improvement of the proposed A-ECMS over other algorithms with similar objectives is that it does not require the knowledge of future driving cycles and has a low computational burden. Results obtained in this research show that the driving conditions can be successfully recognized and good performance can be achieved in various driving conditions while sustaining battery SOC within desired limits.

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