scholarly journals Real-world measurement and mechanical-analysis-based-verification of NO<sub>x</sub> and CO<sub>2</sub> emissions from in-use heavy-duty vehicle

2020 ◽  
Author(s):  
Hiroo Hata ◽  
Kazuo Kokuryo ◽  
Takehiko Ogata ◽  
Masahiko Kugata ◽  
Koichi Yanai ◽  
...  
Keyword(s):  
Real World ◽  
Catalytic Reduction ◽  
Cold Season ◽  
Mechanical Analysis ◽  
Experimental Results ◽  
Emission Measurement ◽  
Heavy Duty ◽  
The Real ◽  
Driving Mode ◽  
Heavy Duty Vehicle

Abstract. A portable emission measurement system (PEMS) was used to measure the real-world driving emissions pertaining to a Japanese middle-sized heavy-duty vehicle. The testing was performed with the vehicle being driven in the metropolitan area of Tokyo in four seasons (January, June, August, and November) to analyze the seasonal dependence of NOx and CO2 emissioans. The experimental results indicated that the amount of NOx emissions was particularly high in the cold season, owing to the slow starting of the NOx detoxification systems, that is, the exhaust gas recirculation and urea-selective-catalytic-reduction systems, under low ambient temperature conditions. In the real-world driving, a high acceleration pattern was observed in the low-speed region, which is not considered in the world harmonized vehicle cycle, which is the worldwide official driving mode in the chassis dynamometer experiment. Finally, the transient emission tables for NOx and CO2 were constructed based on the PEMS measurement results and the classical mechanic theory. The constructed tables well replicated the experimental results in all the considered conditions involving different ambient temperatures and locations. The proposed approach can be used to evaluate emission inventories in the future.

scholarly journals Real-world measurement and mechanical-analysis-based verification of NO<sub><i>x</i></sub> and CO<sub>2</sub> emissions from an in-use heavy-duty vehicle

2021 ◽  
Vol 14 (3) ◽  
pp. 2115-2126
Author(s):  
Hiroo Hata ◽  
Kazuo Kokuryo ◽  
Takehiko Ogata ◽  
Masahiko Kugata ◽  
Koichi Yanai ◽  
...  
Keyword(s):  
Real World ◽  
Catalytic Reduction ◽  
Cold Season ◽  
Mechanical Analysis ◽  
Experimental Results ◽  
Emission Measurement ◽  
Heavy Duty ◽  
Driving Mode ◽  
Ambient Temperatures ◽  
Heavy Duty Vehicle

Abstract. A portable emission measurement system (PEMS) was used to measure the real-world driving emissions pertaining to a Japanese middle-sized heavy-duty vehicle. The testing was performed with the vehicle being driven in the metropolitan area of Tokyo in four seasons (January, June, August, and November) to analyze the seasonal dependence of NOx and CO2 emissions. The experimental results indicated that the amount of NOx emissions was particularly high in the cold season owing to the slow starting of the NOx after-treatment systems, which is to say the exhaust gas recirculation and urea-selective-catalytic-reduction systems, under low-ambient-temperature conditions. In real-world driving, a high acceleration pattern was observed in the low-speed region which is not considered in the world harmonized vehicle cycle, which is the worldwide official driving mode in the chassis dynamometer experiment. Finally, the transient emission tables for NOx and CO2 were constructed based on the PEMS measurement results and the classical mechanic theory. The constructed tables replicated well the experimental results in all the considered conditions involving different ambient temperatures and locations. The proposed approach can be used to evaluate emission inventories in the future.

scholarly journals GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 68
Author(s):  
Lei Shi ◽  
Cosmin Copot ◽  
Steve Vanlanduit
Keyword(s):  
Cognitive Load ◽  
Real World ◽  
Robotic Manipulator ◽  
Similarity Score ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
The Other ◽  
Robot Interaction ◽  
Run Length ◽  
The Real

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.

Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality

2015 ◽  
pp. 73-95 ◽  
Author(s):  
Rafal Rzepka ◽  
Kenji Araki
Keyword(s):  
Text Mining ◽  
Knowledge Base ◽  
Real World ◽  
Semantic Analysis ◽  
Experimental Results ◽  
Artificial Agents ◽  
Knowledge Source ◽  
The Real ◽  
Long Run

This chapter introduces an approach and methods for creating a system that refers to human experiences and thoughts about these experiences in order to ethically evaluate other parties', and in a long run, its own actions. It is shown how applying text mining techniques can enrich machine's knowledge about the real world and how this knowledge could be helpful in the difficult realm of moral relativity. Possibilities of simulating empathy and applying proposed methods to various approaches are introduced together with discussion on the possibility of applying growing knowledge base to artificial agents for particular purposes, from simple housework robots to moral advisors, which could refer to millions of different experiences had by people in various cultures. The experimental results show efficiency improvements when compared to previous research and also discuss the problems with fair evaluation of moral and immoral acts.

scholarly journals In for the Long Haul

1999 ◽  
Vol 121 (02) ◽  
pp. 60-61
Author(s):  
Phil Kittredge ◽  
Thomas Urbas ◽  
Wayne Shintaku
Keyword(s):  
Real Time ◽  
Real World ◽  
Duty Cycle ◽  
Experimental Mechanics ◽  
Heavy Vehicle ◽  
Heavy Duty ◽  
The Real ◽  
Clutch Pedal ◽  
Heavy Duty Truck ◽  
Comprehensive Data

This article focuses on the fact that engineers at Meritor Automotive decided to learn how truck components really held up on the highways. So they outfitted an 18-wheeler with the company’s products for a 24,000-mile trial, in real time and in the real world. According to Meritor, the comprehensive data generated by the test has spurred improvements in brake components, clutches, drivelines, axles, and transmissions. The company claims that the data opens opportunities for improvements in virtually every type of heavy-duty truck component that Meritor builds. The engineers in Meritor’s experimental mechanics unit enlisted support from all the groups in the heavy vehicle division. The use of a channel to record clutch pedal displacement helped engineers improve their model for determining the number of clutch applications in a line-haul duty cycle. Meritor expects that this information will lead to improved durability of several clutch components.

scholarly journals From Reality to Perception: Genre-Based Neural Image Style Transfer

2018 ◽  
Author(s):  
Zhuoqi Ma ◽  
Nannan Wang ◽  
Xinbo Gao ◽  
Jie Li
Keyword(s):  
Transfer Process ◽  
Real World ◽  
Experimental Results ◽  
Style Transfer ◽  
The Real ◽  
Design Aspect ◽  
Semantic Correspondence

We introduce a novel thought for integrating artists’ perceptions on the real world into neural image style transfer process. Conventional approaches commonly migrate color or texture patterns from style image to content image, but the underlying design aspect of the artist always get overlooked. We want to address the in-depth genre style, that how artists perceive the real world and express their perceptions in the artwork. We collect a set of Van Gogh’s paintings and cubist artworks, and their semantically corresponding real world photos. We present a novel genre style transfer framework modeled after the mechanism of actual artwork production. The target style representation is reconstructed based on the semantic correspondence between real world photo and painting, which enable the perception guidance in style transfer. The experimental results demonstrate that our method can capture the overall style of a genre or an artist. We hope that this work provides new insight for including artists’ perceptions into neural style transfer process, and helps people to understand the underlying characters of the artist or the genre.

scholarly journals The Finding and Dynamic Detection of Opinion Leaders in Social Network

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Baocheng Huang ◽  
Guang Yu ◽  
Hamid Reza Karimi
Keyword(s):  
Social Network ◽  
Real World ◽  
Structural Characteristics ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Opinion Leaders ◽  
Data Sources ◽  
The Real ◽  
Data Source ◽  
Different Characteristics

It is valuable for the real world to find the opinion leaders. Because different data sources usually have different characteristics, there does not exist a standard algorithm to find and detect the opinion leaders in different data sources. Every data source has its own structural characteristics, and also has its own detection algorithm to find the opinion leaders. Experimental results show the opinion leaders and theirs characteristics can be found among the comments from the Weibo social network of China, which is like Facebook or Twitter in USA.

scholarly journals Minimizing the average arriving distance in carpooling

2020 ◽  
Vol 16 (1) ◽  
pp. 155014771989936
Author(s):  
Tianlu Zhao ◽  
Yongjian Yang ◽  
En Wang
Keyword(s):  
Air Pollution ◽  
Heuristic Algorithm ◽  
Real World ◽  
Traffic Congestion ◽  
Route Planning ◽  
Experimental Results ◽  
Synthetic Dataset ◽  
Passenger Transport ◽  
The Real ◽  
Vehicle Capacity

The massive use of cars in cities brings several problems such as traffic congestion and air pollution. Carpooling is an effective way to reduce the use of cars on the premise of meeting passenger transport needs. However, route planning will influence the efficiency of carpooling. By now, most researches on the route planning of carpooling mainly pay attention to minimizing the total driving distance of cars, but for passengers, the most crucial thing is to get to the destination as soon as possible. And in most cases, the minimum total driving distance of cars does not mean the minimal average arriving distance of all passengers. To address this issue, in this article, we formulate a novel carpooling route calculation problem with the objective of minimizing the average arriving distance of all passengers in carpooling. Then, we prove that this problem is NP-hard. To solve this problem, for the situation that the vehicle capacity is sufficient to deliver all passengers, we propose a heuristic algorithm named SimilarDirection with [Formula: see text] approximation ratio in delivery order calculation phase, where [Formula: see text] is the capacity of each vehicle. For the situation that the vehicle capacity is insufficient, we provide three algorithms named DelFar, Unchanged, and DelRan. Experimental results show that our SimilarDirection algorithm can produce less average arriving distance of all passengers than other three contrast algorithms in both the real-world dataset experiments and the synthetic dataset experiments, and DelFar has the best performance in producing less average arriving distance when the vehicle capacity is insufficient.

scholarly journals Characterization of Real-World Pollutant Emissions and Fuel Consumption of Heavy-Duty Diesel Trucks with Latest Emissions Control

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 535 ◽  
Author(s):  
Christos Keramydas ◽  
Leonidas Ntziachristos ◽  
Christos Tziourtzioumis ◽  
Georgios Papadopoulos ◽  
Ting-Shek Lo ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Emission Factors ◽  
Pollutant Emissions ◽  
Particulate Filter ◽  
Emission Measurement ◽  
Heavy Duty ◽  
Heavy Duty Diesel ◽  
Diesel Trucks ◽  
The Impact

Heavy-duty diesel trucks (HDDTs) comprise a key source of road transport emissions and energy consumption worldwide mainly due to the growth of road freight traffic during the last two decades. Addressing their air pollutant and greenhouse gas emissions is therefore required, while accurate emission factors are needed to logistically optimize their operation. This study characterizes real-world emissions and fuel consumption (FC) of HDDTs and investigates the factors that affect their performance. Twenty-two diesel-fueled, Euro IV to Euro VI, HDDTs of six different manufacturers were measured in the road network of the Hong Kong metropolitan area, using portable emission measurement systems (PEMS). The testing routes included urban, highway and mixed urban/highway driving. The data collected corresponds to a wide range of driving, operating, and ambient conditions. Real-world distance- and energy-based emission levels are presented in a comparative manner to capture the effect of after-treatment technologies and the role of the evolution of Euro standards on emissions performance. The emission factors’ uncertainty is analyzed. The impact of speed, road grade and vehicle weight loading on FC and emissions is investigated. An analysis of diesel particulate filter (DPF) regenerations and ammonia (NH3) slip events are presented along with the study of Nitrous oxide (N2O) formation. The results reveal deviations of real-world HDDTs emissions from emission limits, as well as the significant impact of different operating and driving factors on their performance. The occasional high levels of N2O emissions from selective catalytic reduction equipped HDDTs is also revealed, an issue that has not been thoroughly considered so far.

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