On the Impact of Prior Experiences in Car-Following Models: Model Development, Computational Efficiency, Comparative Analyses, and Extensive Applications

2021 ◽  
pp. 1-14
Author(s):  
Yang Yu ◽  
Zhengbing He ◽  
Xiaobo Qu
Keyword(s):  
Computational Efficiency ◽  
Model Development ◽  
Comparative Analyses ◽  
Car Following ◽  
Prior Experiences ◽  
The Impact

scholarly journals Modeling Building Stock Development

2021 ◽  
Vol 13 (2) ◽  
pp. 723
Author(s):  
Antti Kurvinen ◽  
Arto Saari ◽  
Juhani Heljo ◽  
Eero Nippala
Keyword(s):  
Model Development ◽  
Housing Demand ◽  
Quality Data ◽  
Building Stock ◽  
Test Arena ◽  
Climate Targets ◽  
Wide Range ◽  
Key Variables ◽  
The Impact

It is widely agreed that dynamics of building stocks are relatively poorly known even if it is recognized to be an important research topic. Better understanding of building stock dynamics and future development is crucial, e.g., for sustainable management of the built environment as various analyses require long-term projections of building stock development. Recognizing the uncertainty in relation to long-term modeling, we propose a transparent calculation-based QuantiSTOCK model for modeling building stock development. Our approach not only provides a tangible tool for understanding development when selected assumptions are valid but also, most importantly, allows for studying the sensitivity of results to alternative developments of the key variables. Therefore, this relatively simple modeling approach provides fruitful grounds for understanding the impact of different key variables, which is needed to facilitate meaningful debate on different housing, land use, and environment-related policies. The QuantiSTOCK model may be extended in numerous ways and lays the groundwork for modeling the future developments of building stocks. The presented model may be used in a wide range of analyses ranging from assessing housing demand at the regional level to providing input for defining sustainable pathways towards climate targets. Due to the availability of high-quality data, the Finnish building stock provided a great test arena for the model development.

Performance Modeling of Desiccant Wheels: 1 — Model Development

2008 ◽  
Author(s):  
Chaoqin Zhai ◽  
David H. Archer ◽  
John C. Fischer
Keyword(s):  
Model Development ◽  
Axial Direction ◽  
Performance Model ◽  
Design Parameters ◽  
Residual Water ◽  
One Dimensional ◽  
Operating Variables ◽  
Steady State Operation ◽  
Rotary Speed ◽  
The Impact

This paper presents the development of an equation based model to simulate the combined heat and mass transfer in the desiccant wheels. The performance model is one dimensional in the axial direction. It applies a lumped formulation in the thickness direction of the desiccant and the substrate. The boundary conditions of this problem represent the inlet outside/process and building exhaust/regeneration air conditions as well as the adiabatic condition of the two ends of the desiccant composite. The solutions of this model are iterated until the wheel reaches periodic steady state operation. The modeling results are obtained as the changes of the outside/process and building exhaust/regeneration air conditions along the wheel depth and the wheel rotation. This performance model relates the wheel’s design parameters, such as the wheel dimension, the channel size and the desiccant properties, and the wheel’s operating variables, such as the rotary speed and the regeneration air flowrate, to its operating performance. The impact of some practical issues, such as wheel purge, residual water in the desiccant and the wheel supporting structure, on the wheel performance has also been investigated.

scholarly journals A Comprehensive Set of Impact Data for Common Aerospace Metals

2017 ◽  
Vol 12 (6) ◽  
Author(s):  
M. R. W. Brake ◽  
P. L. Reu ◽  
D. S. Aragon
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Model Development ◽  
Coefficient Of Restitution ◽  
Image Correlation ◽  
Plastic Behavior ◽  
Data Set ◽  
Force Resolution ◽  
Impact Data ◽  
The Impact

The results of two sets of impact experiments are reported within. To assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution (COR) experiments, in which a 2 m long pendulum is used to study “in-context” measurements of the coefficient of restitution for eight different materials (6061-T6 aluminum, phosphor bronze alloy 510, Hiperco, nitronic 60A, stainless steel 304, titanium, copper, and annealed copper). The coefficient of restitution is measured via two different techniques: digital image correlation (DIC) and laser Doppler vibrometry (LDV). Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are in context as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. The compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and μN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

Technology-Mediated Collaboration, Shared Mental Model and Task Performance

2012 ◽  
Vol 24 (1) ◽  
pp. 64-81 ◽  
Author(s):  
Hayward P. Andres
Keyword(s):  
Social Influence ◽  
Direct Observation ◽  
Mental Model ◽  
Social Impact ◽  
Model Development ◽  
Research Approach ◽  
Team Process ◽  
Shared Mental Model ◽  
Team Productivity ◽  
The Impact

This study takes a direct observation research approach to examine how the impact of collaboration mode on team productivity and process satisfaction is mediated by shared mental model. Team cognition and social impact theories are integrated to provide a framework for explaining how technology-mediated collaboration constrains or enhances team shared mental model development and its subsequent impact on task outcomes. Partial least squares analysis revealed that technology-mediated collaboration impacts shared mental model development. The results also demonstrate that timely and accurate development of shared mental model facilitates increases in both productivity and team process satisfaction. Direct observation of team process behaviors suggests that collaboration modes differ not only in their impact on communication facilitation but efficacy-based, motivational, and social influence factors (e.g., self-efficacy and team-efficacy, perceived salience and credibility of contributions, social influence on action, etc.) as well. Shared mental model development requires quality communication among team members that are motivated to participate by a positive team climate that promotes idea convergence.

A Comparative Study of Data and Physically Based Gas Turbine Modeling for Long-Term Monitoring Scenarios: Part II — Emission Prediction Utilizing Different Levels of Design Information

2018 ◽  
Author(s):  
Moritz Lipperheide ◽  
Thomas Bexten ◽  
Manfred Wirsum ◽  
Martin Gassner ◽  
Stefano Bernero
Keyword(s):  
Gas Turbine ◽  
A Priori ◽  
Model Development ◽  
Fine Tuning ◽  
Plant Operator ◽  
Engine Model ◽  
Physically Based ◽  
Design Type ◽  
The Impact

Reliable engine and emission models allow for an online monitoring of commercial gas turbine operation and help the plant operator and the original equipment manufacturer (OEM) to ensure emission compliance of the aging engine. However, model development and validation require fine-tuning on the particular engines, which may differ in a fleet of a single design type by production, assembly and aging status. For this purpose, Artificial Neural Networks (ANN) offer a good and fast alternative to traditional physically-based engine modeling, because the model creation and adaption is merely an automatized process in commercially available software environments. However, ANN performance depends strongly on the availability of suitable data and a-priori data processing. The present work investigates the impact of specific engine information from the OEM’s design tools on ANN performance. As an alternative to a strictly data-based benchmark approach, engine characteristics were incorporated into ANNs by a pre-processing of the raw measurements with a simplified engine model. The resulting ‘virtual’ measurements, i.e. hot gas temperatures, then served as inputs to ANN training and application during long-term gas turbine operation. When processed input parameters were used for ANNs, overall long-term NOx prediction improved by 55%, and CO prediction by 16% in terms of RMSE, yielding comparable overall RMSE values to the physically-based model.

scholarly journals A New Car-Following Model with Consideration of Dynamic Safety Distance

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Tao Wang ◽  
Jing Zhang ◽  
Guangyao Li ◽  
Keyu Xu ◽  
Shubin Li
Keyword(s):  
Traffic Flow ◽  
Velocity Model ◽  
Safe Distance ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Safety Distance ◽  
Car Following Model ◽  
The Impact

In the traditional optimal velocity model, safe distance is usually a constant, which, however, is not representative of actual traffic conditions. This paper attempts to study the impact of dynamic safety distance on vehicular stream through a car-following model. Firstly, a new car-following model is proposed, in which the traditional safety distance is replaced by a dynamic term. Then, the phase diagram in the headway, speed, and sensitivity spaces is given to illustrate the impact of a variable safe distance on traffic flow. Finally, numerical methods are conducted to examine the performance of the proposed model with regard to two aspects: compared with the optimal velocity model, the new model can suppress traffic congestion effectively and, for different safety distances, the dynamic safety distance can improve the stability of vehicular stream. Simulation results suggest that the new model is able to enhance traffic flow stability.

An improved car-following model considering the impact of safety messages

2018 ◽  
Vol 32 (32) ◽  
pp. 1850398 ◽  
Author(s):  
Tenglong Li ◽  
Fei Hui ◽  
Xiangmo Zhao
Keyword(s):  
Traffic Congestion ◽  
Dominant Factor ◽  
Velocity Difference ◽  
Car Following ◽  
Safety Message ◽  
Warning Messages ◽  
Gray Correlation ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.

scholarly journals Effects of Climate Change on Grassland Biodiversity and Productivity: The Need for a Diversity of Models

2017 ◽  
Author(s):  
Marcel van Oijen ◽  
Gianni Bellocchi ◽  
Mats Höglind
Keyword(s):  
Climate Change ◽  
Model Development ◽  
Grassland Ecosystems ◽  
Climatic Impacts ◽  
Grassland Productivity ◽  
Climatic Responses ◽  
High Level ◽  
The Impact ◽  
Grassland Biodiversity

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types.

scholarly journals Vehicle-to-Vehicle Radio Channel Characteristics for Congestion Scenario in Dense Urban Region at 5.9 GHz

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yishui Shui ◽  
Fang Li ◽  
Junyi Yu ◽  
Wei Chen ◽  
Changzhen Li ◽  
...  
Keyword(s):  
Communication Systems ◽  
Radio Channel ◽  
Average Power ◽  
Urban Region ◽  
Doppler Spectrum ◽  
Small Scale ◽  
Power Delay Profile ◽  
Car Following ◽  
Vehicle To Vehicle ◽  
The Impact

This paper reports the results of a car-following measurement of the wireless propagation channel at 5.9 GHz on a seriously congested urban road in Wuhan, China. The small-scale amplitude-fading distribution was determined to be a Ricean distribution using the Akaike information criterion. This result shows that this car-following scenario can be regarded as a line-of-sight radio channel. Moreover, the statistical K-factor features follow a Gaussian distribution. According to the power delay profile and average power delay profile, we found that street buildings in this dense urban environment contributed to very strong reflection phenomena. The impact of a powerful reflection is analyzed through path loss, delay, and Doppler spreads in the channel statistical properties. In the frequency domain, we observe a U-shape delay-Doppler spectrum that proved that the dense urban scenario consists of scattering channels. All these results are summarized in tabular form that will be useful in the modeling of vehicle-to-vehicle wireless communication systems.

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