Many researchers have investigated the effect of alloying elements on the properties of high-strength steels. Vanadium is of great importance due to its positive effect on solid solution strengthening, precipitation hardening, and grain boundary refinement, but the effect of this element on the properties of delta-TRIP steel has not been investigated independently, therefore, in this reserch, the effect of adding 0.12 and 0.25 wt.% vanadium on the microstructure and mechanical properties of a Delta-TRIP steel has been studied.  The structure of the three steels before applying the heat treatment cycle consisted of delta-ferrite, allotriomorphic ferrite, martensite, and pearlite. The heat treatment cycle led to the stability of the austenite phase. The addition of 0.12 wt.% V resulted in the enhancement of the mechanical properties so that the best combination of strength (866 MPa) and elongation percentage (41%) was achieved in this steel. Nonetheless, the addition of 0.25 wt.% V deteriorated the mechanical properties since the increase in the vanadium content promoted the formation of martensite, decreased the percentage of the retained austenite, and weakened the mechanical properties. However, adding 0.12 wt.% V improved the mechanical properties since it increased the strength through solid-solution strengthening and precipitation hardening; no brittle martensite was formed, and lamellar δ-ferrite was achieved. The steel containing 0.12 wt.% V, exhibiting a formability index of 35700 MPa%, is in the range of third-generation advanced high-strength steels.

Decision on policies such as the ban on vehicles traffic or on a specific day, parking charges and the possibility of variable work hours requires behavioral studies sensitive to this kind of policies which activity-based approach tries to create a suitable tool for with regard to time and space of people activities and their plan. TRIP chain planning in such a way that people, especially in metropolitans, travel sequentially and without any need to return home is an attempt to save time and money, that this paper deals with mathematical modeling. Modeling the selection of TRIP chain pattern and interpretation of relevant variables are the main objective of the current paper which in order to implement the model empirically and quantitatively, data obtained from inquiry a sample of Qazvin residents (including personal and household characteristics) and the characteristics of transport networks and features of vulnerable sites for doing tasks is used. Selecting TRIP chain pattern of people with separated travel purpose is done by Multinomial Logit Model and factors affecting the selection of different types of TRIP chain pattern in three-TRIP tours is examined. The results show that the average travel time, passenger age, gender, car ownership, walking, business rates of one’s residential place, employment and per-capita vehicle ownership in the origin area are the various factors affecting the choice of the TRIP chain pattern. Such models and this analysis can help transport managers and policy makers in different management policies to improve traffic conditions by providing useful and needed information.

This paper examines the structure of traveler behavior and how it can be measured using a set of survey questions. In this context، senses of place factors were extracted using a three-tiered، structural equation model، which simultaneously estimated three factors: Attitude، Lifestyle and shopping orientation. Through this research we have been able to both transfer successful questions measuring well accepted behavior constructs and examine further place attributes contribution. However، it is necessary to further this research and the preliminary findings of this exploratory analysis. All three factors need to be verified in future studies for their ability to explain behavior، and should be examined in different everyday activity settings to compare the strength of the manifested factors across types of activities and settings. In parallel، qualitative analysis can be used to enhance the understanding of these concepts. Although several socio-demographic characteristics were shown to be attitudes، these indicators are only able to explain a small subset of the variation، and the rich nature of behavior may require more in-depth scrutiny of their formation as well as other determinants. This study is limited to behavior about one specific location studied (Bazar)، and within a short period of a day’ s activities. Future research should be conducted to determine if there are aspects of behavior and their development that might be predicted more completely using socio-demographic indicators. The idea of applying these variables in modeling the individual clothes shopping destination choice by using structure equation models was sourced from ethology studies on customers of shopping centers (novelty of paper). In this paper 213 samples are collected by internet-based questionnaire and individuals socio-economic، attitude، lifestyle and shopping orientation were asked. This integrated model is able to correctly predict the 68. 1 percent of observation has the highest percent correct.

Various parameters affect the number of household TRIPs, therefore it can be claimed that the first step in the modeling of TRIP-generation is identification of the most important of these parameters. In this research the effective parameters on TRIP-generation are determined and evaluated by using the rough-set approach as a modern mathematical method. The primary purpose of the present paper is to find the smallest sets of attributes having quality equal to the general quality of the defined characteristics in the information system. So, the number of parameters used in the modeling is reduced. To evaluate the results, the best algorithm of the defined attributes in the information system is identified by making use of the stepwise (stepwise linear regression) method and then compares the results with each other. The results of the research indicate that the rough-set theory has a better and stronger operational capability in identifying the effective parameters in TRIP-generation modeling. By taking advantage of these results, the amount of necessary data for TRIP-generation modeling is decreased and the speed and effectiveness of information processing are increased considerably.

TRIP steels are one type of advanced high strength steels and the application them is increasing because of their good strength and formability. The special microstructure of TRIP steel can be obtained by a two stage heat treatment contains intercritical annealing (IA) and intermediate ageing. The temperatures of these two stages have important effect on microstructure and mechanical properties of TRIP steels. In this paper the effect of heat treatment temperature on microstructure and mechanical properties of steels with chemical composition of Fe-0.2C-1.5Si-1.5Mn was investigated. The temperatures of 770, 790 and 810 C for IA and 330, 350 and 370 C for intermediate aging were selected. XRd test was applied to determine the austenite volume fraction of microstructure. For measurement of strength and elongation of cases, tensile test was used and then the results were discussed by thermodynamic calculations. By the increasing of intercritical annealing temperature the volume fraction of austenite, its carbon and the strength of steels increased at first and then were decrease. Increasing of intermediate ageing temperature caused to decreasing of austenite volume fraction, its carbon content, strength and elongation of cases.

The paper focuses attention on the influence life cycle stages exerts on travel behavior. It presents the family Life cycle concept and its usefulness in the TRIP generation phase of the urban transportation planning process. The concept refers to the household structure reflected in life cycle stages expressed as the major break points through which a household passes as it evolves. A life cycle classification scheme is formulated using available data from the city of Shiraz in Iran to better explain travel behavior. Different stages in the household life cycle (or family structure) consistent with significant changes of activity time allocation and travel behavior are identified. Disaggregate behavioral TRIP generation models which incorporate a wide spectrum of independent variables such as household socioeconomic characteristics, family structure and life cycle stage, and land use attributes of residence location were pursued. Based on the assumption of the stage in the life cycle, it is found that there is a significant effect on the estimated number of TRIPs made for different purposes. Stepwise regression analysis is used to test the adequacy of the life cycle based model. Results demonstrate the usefulness of the family life cycle variables in replicating travel behavior through the disaggregate TRIP generation models.