Placeholder image for staff profiles

Arvind Tiwari


Postgraduate Research Student
M. Tech (Environmental Engineering & Management); B.E. (Civil Engineering)
+44 (0)1483 686657
22 AA 03
10:00 AM to 05:00 PM

Biography

Arvind Tiwari is a Post graduate researcher (PhD Student) that holds a Post graduate degree in Environmental & management from Indian institute of Technology Delhi (IIT-D) and Under graduate degree in Civil Engineering from Madhav institute of technology & Science Gwalior, India. He has six year work experience in Modelling and simulation of environmental  flow problems and currently is a PhD student in Civil and Environmental Engineering at University of Surrey.  During his stay in Guildford, He will be under the guidance of Prof. Prashant Kumar (Principle Supervisor) and Dr. Devendra Saroj (Co- Supervisor) on the topic: Air Pollutants Transport Modelling of nano-particles in urban environment.

My qualifications

2 Year (Master of Technology)
Post graduate degree in Environmental & management
Indian institute of Technology Delhi (IITD), INDIA
4 Year (Bachelor of Engineering)
Under graduate degree in Civil Engineering
Madhav institute of Technology & Science (MITS), INDIA

Courses I teach on

Undergraduate

My publications

Publications

Quintana - Amate S, Bermell - Garcia P, Tiwari Arind, Turner C J (2016) A new knowledge sourcing framework for knowledge-based engineering: An aerospace industry case study, Computers & Industrial Engineering 104 pp. 35-50 Elsevier
New trends in Knowledge-Based Engineering (KBE) highlight the need for decoupling the automation aspect from the knowledge management side of KBE. In this direction, some authors argue that KBE is capable of effectively capturing, retaining and reusing engineering knowledge. However, there are some limitations associated with some aspects of KBE that present a barrier to deliver the knowledge sourcing process requested by industry. To overcome some of these limitations this research proposes a new methodology for efficient knowledge capture and effective management of the complete knowledge life cycle. The methodology proposed in this research is validated through the development and implementation of a case study involving the optimisation of wing design concepts at an Aerospace manufacturer. The results obtained proved the extended KBE capability for fast and effective knowledge sourcing. This evidence was provided by the experts working in the development of the case study through the implementation of structured quantitative and qualitative analyses.
Gonzalez Lozano G., Tiwari A., Turner C. (2018) A design algorithm to model fibre paths for manufacturing of structurally optimised composite laminates, Composite Structures 204 pp. 882-895 Elsevier
Fibre steering is involved in the development of non-conventional variable stiffness laminates (VSL) with curvilinear paths as well as in the lay-up of conventional laminates with complex shapes. Manufacturability is generally overlooked in design and, as a result, industrial applications do not take advantage of the potential of composite materials. This work develops a design for manufacturing (DFM) tool for the introduction in design of the manufacturing requirements and limitations derived from the fibre placement technology. This tool enables the automatic generation of continuous fibre paths for manufacturing. Results from its application to a plate with a central hole and an aircraft structure ? a windshield front fairing ? are presented, showing good correlation of resulting manufacturable paths to initial fibre trajectories. The effect of manufacturing constraints is assessed to elucidate the extent to which the structurally optimal design can be reached while conforming to existing manufacturing specifications.
Tiwari Arvind, Kumar Prashant, Baldauf Richard, Zhang K. Max, Pilla Francesco, Di Sabatino Silvana, Brattich Erika, Pulvirenti Beatrice (2019) Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models, SCIENCE OF THE TOTAL ENVIRONMENT 672 pp. 410-426 ELSEVIER SCIENCE BV
Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales ? microscale (i.e. 10?500/m) and macroscale (i.e. 5?100/km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.
Tiwari Arvind, Kumar Prashant, Baldauf Richard, Zhang K. Max, Pilla Francesco, Di Sabatino Silvana, Brattich Erika, Pulvirenti Beatrice (2019) Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models, Science of The Total Environment 672 pp. 410-426 Elsevier
Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales ? microscale (i.e. 10?500/m) and macroscale (i.e. 5?100/km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.
Kumar Prashant, Druckman Angela, Gallagher John, Gatersleben Birgitta, Allison Sarah, Eisenman Theodore S., Hoang Uy, Hama Sarkawt, Tiwari Arvind, Sharma Ashish, Abhijith K V, Adlakha Deepti, McNabola Aonghus, Astell-Burt Thomas, Feng Xiaoqi, Skeldon Anne, de Lusignan Simon, Morawska Lidia (2019) The Nexus between Air Pollution, Green Infrastructure and Human Health, Environment International Elsevier
Cities are constantly evolving and so are the living conditions within and between them. Rapid urbanization and the ever-growing need for housing have turned large areas of many cities into concrete landscapes that lack greenery. Green infrastructure can support human health, provide socio-economic and environmental benefits, and bring color to an otherwise grey urban landscape. Sometimes, benefits come with downsides in relation to its impact on air quality and human health, requiring suitable data and guidelines to implement effective greening strategies. Air pollution and human health, as well as green infrastructure and human health, are often studied together. Linking green infrastructure with air quality and human health together is a unique aspect of this article. A holistic understanding of these links is key to enabling policymakers and urban planners to make informed decisions. By critically evaluating the link between green infrastructure and human health via air pollution mitigation, we also discuss if our existing understanding of such interventions is enabling their uptake in practice.

Both the natural science and epidemiology approach the topic of green infrastructure and human health very differently. The pathways linking health benefits to pollution reduction by urban vegetation remain unclear and that the mode of green infrastructure deployment is critical to avoid unintended consequences. Strategic deployment of green infrastructure may reduce downwind pollution exposure. However, the development of bespoke design guidelines is vital to promote and optimize greening benefits and measuring green infrastructure?s socio-economic and health benefits are key for their uptake. Greening cities to mitigate pollution effects is on the rise and these needs to be matched by scientific evidence and appropriate guidelines. We conclude that urban vegetation can facilitate broad health benefits, but there is little empirical evidence linking these benefits to air pollution reduction by urban vegetation, and appreciable efforts are needed to establish the underlying policies, design and engineering guidelines governing its deployment.