Warren Jasper
Bio
AccomplishmentsResearch
Teaching
Additional Information
Google Scholar
Education
BS Massachusetts Institute of Technology
MS Massachusetts Institute of Technology
PhD Stanford University
Area(s) of Expertise
Sustainability
Technical/Electronic Textiles/Wearables
Textile Engineering
Publications
- A review of deep learning and artificial intelligence in dyeing, printing and finishing , TEXTILE RESEARCH JOURNAL (2024)
- A review of deep learning within the framework of artificial intelligence for enhanced fiber and yarn quality , TEXTILE RESEARCH JOURNAL (2024)
- A theoretical model to investigate the performance of cellulose yarns constrained to lie on a moving solid cylinder , Cellulose (2020)
- A generalized variational approach for predicting contact angles of sessile nano-droplets on both flat and curved surfaces , JOURNAL OF MOLECULAR LIQUIDS (2019)
- An Application of Lean Six Sigma in Cotton Yarn Dyeing , AATCC Review (2019)
- Incorporating wireless data acquisition into the STEM Curriculum: A case study with Lean Six Sigma , 2019 ASEE Southeastern Section Conference (2019)
- Plasma textiles as fibrous filter media , Fibrous Filter Media (2017)
- Real-time dyebath monitoring of reactive dyeing on cationized cotton for levelness control: part 2-effects of leveling agents and dye dosing , CELLULOSE (2017)
- Relationship between contact angle and contact line radius for micro to atto [10(-6) to 10(-18)] liter size oil droplets , JOURNAL OF MOLECULAR LIQUIDS (2017)
- Modeling of submicron particle filtration in an electret monolith filter with rectangular cross-section microchannels , AEROSOL SCIENCE AND TECHNOLOGY (2016)
Grants
The goal of these projects are to provide a report including recommendations with sound justification from research data to identify ways to enhance existing wildland personal protective equipment provided to wildland firefighters to better protect against the various elements they are exposed to in the course of their firefighting operations in the WUI.
Since it was originally issued over a decade ago, no respiratory protection devices have been manufactured or submitted for certification under the NFPA 1984 Standard on Respirators for Wildland Fire-Fighting and Wildland Urban Interface Operations. In 2016, NIOSH presented to the NFPA Technical and Correlating Committee the barriers to acceptance, adoption, and implementation. While agencies agreed that the performance standards were appropriate for wildland exposures and that technology existed to produce a certifiable product, the main reason manufacturers had not submitted a product for certification was that there was no perceived market for the device since no firefighting management agencies required firefighters to utilize respiratory protection. Indeed, federal wildland agencies cannot require PPE until NFPA 1984 compliant devices are available. The newly released 2022 standard provides greater clarity on the goals and criteria, with increased recognition of risk in the WUI, however many of the same barriers to understanding, acceptance, and adoption continue to be relevant today. This project will help overcome this significant disconnect through an interdisciplinary and collaborative program that provides a national-scale education, training, and implementation campaign that brings together fire agencies, manufacturers, regulatory agencies, and subject matter experts to facilitate understanding, acceptance, and adoption of wildland/WUI respiratory protection.
The Scholle lab will be responsible for testing a plasma textile filter developed by Warren Jasper at NCSU and Stitchpartners for its ability to eliminate aerosolized coronaviruses. The Scholle lab will aerosolize the virus in a glove box with the filter, collect samples and analyze the presence of virus using RT-PCR methodology.
Several recent studies at NC State University focusing on resourcing textile and apparel manufacturing in the US indicated two major barriers: cost and quality. By combining several operations in the supply chain, companies are discovering new economies of scale. One of the most promising areas of process improvement is in dyeing and finishing Current dyeing and finishing operations are water and energy intensive. Studies have shown that most current dyeing operations could reduce total water consumption by 20%, energy by 25% and time (labor, machine utilization) by as much as 30% with no major capital outlays through strategic changes in processes, procedures and methodologies. Additionally, dyeing operations produce effluent containing salt, dyes, surfactants, and other chemicals that must be treated to meet environmental standards and regulations adding additional costs to U.S. manufacturing companies. The greatest impediment for the dyer in achieving a sustainable manufacturing process is the false impression that any changes to existing methods are costly, capital intensive or ineffective. Leading companies throughout the world are using Lean Six Sigma (LSS) to reduce manufacturing costs, improve quality and reduce cycle times. But these Lean Six Sigma methodologies have not been widely used in yarn and fabric dyeing due to the lack of instrumentation to measure and monitor two key components in dyeing: color and water. For any major quality improvement initiative, key inputs and outputs must be measured, either directly or indirectly to affect the desired change. This is a paradigm shift from current practices, where minimal data on dyes and the dyeing process are acquired and analyzed during commercial operations. There exits few instruments capable of measuring color during the dyeing process. Although many companies want to reduce water and energy consumption, they are reluctant to invest the human and monetary capital to affect changes in their current dyeing processes without proof of the results that can be achieved. There are also very few studies documenting the potential savings of using a LSS approach, ROI, and total cost savings. Thus the perceived risk in adopting a LSS approach to dyeing fabric coupled with measurements and monitoring of the dyeing process outweighs the perceived benefits and so this approach has not been embraced by the industry. This project proposes to demonstrate the actual cost savings that could be realized by a manufacturing plant by adopting a LSS approach to dyeing and implementing real-time measurements to measure dye strength, water utilization, dye-uptake or exhaustion, and fixation. Baseline measurements of water, energy, dye-strength, and exhaustion will be acquired by use of instruments capable of measuring dye absorbance in real-time. After baseline data of the dyeing process is acquired, we propose to implement an onsite LSS process with key engineering personnel focused on optimizing the dyeing process using the DMAIC (Design, Measure, Analyze, Improve and Control) methodology to reduce water, energy, and dye in production. Total cost savings will be analyzed. The outcomes will be hardened instrumentation capable of measuring dye utilization as well as water and energy utilization in the dyeing process, and a LSS methodology in place to use this data to improve the dyeing process by reducing water consumption, energy, and effluent. During these experiments we will also explore how improving the dyeing processes can lead to further improvements in the supply chain leading to new opportunities for U.S.-based manufacturing.
Grading or determining the amount of OPD is somewhat subjective, and requires a skilled technician to make this determination. The proposal will investigate ways to automate this process, and algorithmically determine to degree of OPD in a film.
Proof of principle study of using a textile embedded corona discharge in combination with optical emission spectrscopy to detect chemical and radiological hazards in air.
We propose to investigate the effects of Brownian motion and electrostatic charge (both in the particle and on the surface of the filter) on submicron particles (< 300 nm) in airflows containing laminar flow monolith filters with open channels of 0.5-5um in diameter. A monolith filter, where an aerosol flow is filtered in circular channels, insures a high surface to volume ratio, which improves overall filtration efficiencies as particle capture occurs on the surface of the membrane. Improved filtration efficiencies at lower pressure drops can be obtained by charging either the particles, the filter, or both. Charge on the filter surface can induce a dipole on uncharged particles, and electrostatically attract the particle to the surface of the monolith, thus improving capture efficiency.
The primary goal of the proposed research is to develop an accurate and precise integrated color control system that can be easily implemented throughout the US textile industrial manufacturing complex, from product designer through to merchandiser, dyer, retailer and consumer. Fundamental research in the following areas must be addressed to achieve this goal: 1) Develop illuminant data that correlate with the color rendering of lighting used in standard light booths (especially daylight simulators) and lighting used in retail stores, 2) Develop an accurate color inconstancy model and integrate it into color formulation software, 3) Establish the minimum possible error in color difference assessment via a well-controlled, statistically valid color difference experiment that is replicated by at least 3 independent observe panels from different regions of the world (U.S., Asia and Europe).