Product Performance Evolution Prediction by Lotka-Volterra Equations

2017 ◽  
Author(s):  
Guanglu Zhang ◽  
Daniel A. McAdams ◽  
Milad Mohammadi Darani ◽  
Venkatesh Shankar
Keyword(s):  
Time History ◽  
Evaluation Process ◽  
Development Planning ◽  
Performance Data ◽  
Product Performance ◽  
Volterra Equations ◽  
Performance Impact ◽  
Frame Design ◽  
Curve Model ◽  
S Curve

During the development planning of a new product, designers rely on the prediction of the product performance to make business investments and frame design strategy. The S-curve model is commonly used for this purpose, but it has several drawbacks. A significant volume of product performance data doesn’t fit well with an S-curve. An S-curve model is also not capable of showing what factors shape the future performance of a product and how designers can change it. In this paper, Lotka-Volterra equations, which subsume both the logistic S-curve model and Moore’s Law, are used to describe the interaction between a product (system technology) and the components and elements (component technologies) that are combined to form the product. The equations are simplified by a relationship table and a maturation evaluation process as a two-step simplification. The historical performance data of the system and its components are fitted by the simplified Lotka-Volterra equations. The methods developed here allow designers to predict the performances of a product and its components quantitatively by the simplified Lotka-Volterra equations. The methods also shed light on the extent of performance impact from a specific module on a product, which is valuable for identifying the key features of a product and thus making outsourcing decisions. Smart phones are used as an example to demonstrate the two-step simplification. The data fitting method is validated by the time history performance data of airliners and turbofan aero-engines.

scholarly journals Technology Evolution Prediction Using Lotka–Volterra Equations

2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Guanglu Zhang ◽  
Daniel A. McAdams ◽  
Venkatesh Shankar ◽  
Milad Mohammadi Darani
Keyword(s):  
Development Planning ◽  
Component Technology ◽  
Volterra Model ◽  
Volterra Equations ◽  
System Technology ◽  
Product System ◽  
Performance Impact ◽  
Technology Evolution ◽  
S Curve

During the development planning of a new product, designers and entrepreneurs rely on the prediction of product performance to make business investment and design strategy decisions. Moore's law and the logistic S-curve model help make such predictions but suffer several drawbacks. In this paper, Lotka–Volterra equations are used to describe the interaction between a product (system technology) and the components and elements (component technologies) that are combined to form the product. The equations are simplified by a relationship table and maturation evaluation in a two-step process. The performance data of the system and its components over time are modeled by simplified Lotka–Volterra equations. The methods developed here allow designers, entrepreneurs, and policy makers to predict the performances of a product and its components quantitatively using the simplified Lotka–Volterra equations. The methods also shed light on the extent of performance impact from a specific module (component technology) on a product (system technology), which is valuable for identifying the key features of a product and for making outsourcing decisions. Smartphones are used as an example to demonstrate the two-step simplification process. The Lotka–Volterra model of technology evolution is validated by a case study of passenger airplanes and turbofan aero-engines. The case study shows that the data fitting and predictive performances of Lotka–Volterra equations exceed those of extant models.

A Development of the Visco-Elastic Damper for Timber Structure and a Suggestion of the Technological Design Assistance System

2013 ◽  
Vol 778 ◽  
pp. 714-721
Author(s):  
Katsuhiko Kohara ◽  
Takeshi Nomura ◽  
Kazuyoshi Koumoto
Keyword(s):  
Seismic Response ◽  
Elastic Body ◽  
Structural Model ◽  
Time History ◽  
Timber Structure ◽  
Response Analysis ◽  
Frame Design ◽  
Timber Frame ◽  
Loading Tests ◽  
Controlled Structure

Our research team developed a brace type and an angle brace type of the visco-elastic damper on seismic-response controlled structure for timber structure. We performed various dependence evaluations by the materials examination of the styrene olefin-based visco-elastic body which we developed newly. We made a structural model using the performance that loading tests in timber frame. We inspected the validity of the structural model. In addition, we built a technical support system for damper setting by the time history response analysis so that a general design architect was easy to use the damper. We could express dynamics properties of visco-elastic body properties by Voigt model, and the structural model almost accorded with an examination property value. We made a structural model of the whole frame system by Kb of installation rigidity obtained from loading tests in timber frame. Because a design level almost accorded with experimental value, the validity of the frame design on seismic-response controlled structure in consideration of the dependence (distortion, frequency, temperature) of the visco-elastic body was confirmed. This visco-elastic damper on seismic-response controlled structure acquired minister authorization of Ministry of Land, Infrastructure and Transport. In addition, this damper acquired the certification of the Japan Building Disaster Prevention Association.

S-curve Model of Relationship Between Energy Consumption and Economic Development

2014 ◽  
Vol 24 (1) ◽  
pp. 53-64 ◽  
Author(s):  
Anjian Wang ◽  
Gaoshang Wang ◽  
Qishen Chen ◽  
Wenjia Yu ◽  
Kun Yan ◽  
...  
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Curve Model ◽  
S Curve

DYNAMIC SIMULATION MODEL FOR SUSTAINABLE MUNICIPALITY DEVELOPMENT IN VIDZEME REGION, LATVIA

2017 ◽  
Vol 2 ◽  
pp. 11
Author(s):  
Aigars Andersons ◽  
Sarmite Rozentale
Keyword(s):  
Sustainable Development ◽  
Simulation Model ◽  
Dynamic Simulation ◽  
Evaluation Process ◽  
Monitoring And Evaluation ◽  
Simulation Modelling ◽  
Development Planning ◽  
System Dynamic ◽  
Dynamic Simulation Model ◽  
System Dynamic Simulation

Authors in this research paper publish the results of system dynamic simulation modelling in the field of sustainable development planning, monitoring and evaluation for all 26 Latvia Vidzeme region municipalities. As the most notable research outcome, authors created original socio-technical system dynamic simulation model in STELLA modelling environment valid for sustainable development evaluation purposes. After successful verification and validation process of this model authors reached the significant results for improved methodology of dynamic systems evaluation process reliability of sustainable development in Vidzeme region municipalities. Methodology, proposed by authors roots into the quantitative statistical data analysis and system dynamic process simulation modelling.

Uncertain Technology Evolution and Decision Making in Design

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Jonathan L. Arendt ◽  
Daniel A. McAdams ◽  
Richard J. Malak
Keyword(s):  
Research And Development ◽  
Pareto Frontier ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Development Effort ◽  
Technology Evolution ◽  
Curve Model ◽  
S Curve ◽  
Over Time

The potential for engineering technology to evolve over time can be a critical consideration in design decisions that involve long-term commitments. Investments in manufacturing equipment, contractual relationships, and other factors can make it difficult for engineering firms to backtrack once they have chosen one technology over others. Although engineering technologies tend to improve in performance over time, competing technologies can evolve at different rates and details about how a technology might evolve are generally uncertain. In this article we present a general framework for modeling and making decisions about evolving technologies under uncertainty. In this research, the evolution of technology performance is modeled as an S-curve; the performance evolves slowly at first, quickly during heavy research and development effort, and slowly again as the performance approaches its limits. We extend the existing single-attribute S-curve model to the case of technologies with multiple performance attributes. By combining an S-curve evolutionary model for each attribute with a Pareto frontier representation of the optimal implementations of a technology at a particular point in time, we can project how the Pareto frontier will move over time as a technology evolves. Designer uncertainty about the precise shape of the S-curve model is considered through a Monte Carlo simulation of the evolutionary process. To demonstrate how designers can apply the framework, we consider the scenario of a green power generation company deciding between competing wind turbine technologies. Wind turbines, like many other technologies, are currently evolving as research and development efforts improve performance. The engineering example demonstrates how the multi-attribute technology evolution modeling technique provides designers with greater insight into critical uncertainties present in long-term decision problems.

scholarly journals The analysis of performance level on an existing multi-story building structure using the time history based on the subduction earthquake source

2020 ◽  
Vol 156 ◽  
pp. 05011
Author(s):  
Wisnu Erlangga ◽  
Mochamad Teguh ◽  
Lalu Makrup
Keyword(s):  
Time History ◽  
Evaluation Process ◽  
Response Spectra ◽  
Performance Level ◽  
Subduction Earthquake ◽  
Earthquake Sources ◽  
Use Of Time ◽  
Matching Process ◽  
Immediate Occupancy ◽  
Analysis Of Performance

The use of time history in the building evaluation process is rarely done. Usually, the time history used is taken from a different location, with the building being evaluated so that the evaluation results become less valid. Each place has a different time history character that is why the analysis of structures using time history from other sites is not accurate. In this study, the time history used was sourced from subduction earthquake sources. For the time history used in the location of the study, a spectral matching process is needed to equalize the response spectra of the time history with the response spectra at the study location. The Alana Hotel is selected as a research object for building evaluation adopting SNI 03-1726-2012, FEMA 356, and ATC-40 as references with structural modeling using SAP2000. Based on the evaluation results, it can be summarized that displacement values at each floor do not exceed the maximum limit so that this building has fulfilled the requirements. The inter-level displacement due to earthquake loading does not exceed the limit so that this building is feasibly occupied. The performance level of the Alana Hotel is Immediate Occupancy (IO).

An Updated Trend Analysis Representing the Outbreak of Novel Coronavirus (2019-nCoV) in 16 Cities of Hubei Province, China Using Logistic S-Curve Model

2020 ◽  
Author(s):  
Muhammad Fawad ◽  
Sumaira Mubarik ◽  
Saima Shakil Malik ◽  
Yangyang Hao ◽  
Chuanhua Yu ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Hubei Province ◽  
Curve Model ◽  
S Curve ◽  
Novel Coronavirus
Sign in / Sign up

Export Citation Format

Share Document