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STEM I with Scientific and Technical Writing

STEM I is a rigorous course that is taught by Dr. Crowthers. The largest aspect of this class is our independent research project. Starting in August, we began brainstorming and completing initial background research. Projects can be in science, engineering, or mathematics. Throughout the school year, we are guided by Dr. C through stages of literature review, creating hypotheses, organizing our project, and writing numerous technical pieces including a grant proposal and a thesis. Additionally, we are lectured by research professionals in numerous fields about the research process.

Utilizing Digital Twin Modeling Technology to Determine the Optimal Recycled Material to be Used as Building Insulation

Insulation, while necessary to maintain the temperatures inside our homes, can cause additional waste and pollution. This project aims to use a digital twin, a subset of building information modeling, to model different recycled materials as insulation.

Abstract

This project’s objective is to utilize digital twin technology to determine an optimal recycled material to use as building insulation. The project identifies what recycled material best insulates a building, through the use of a digital twin to model insulation properties. If digital twin technology is utilized to determine the heat loss and insulation efficiency of various recycled insulation materials, homes can be kept warm while also reducing waste. Since ancient times, the use of environmentally available materials such as mud, cork, and asbestos as insulation kept living spaces at desired temperatures all over the world. However, the use of these traditional types of insulation can be harmful to the environment. Digital twins, a subset of Building Information Modeling, are digital replicas of physical assets. In this project, COMSOL Multiphysics modeling software was used to represent the digital twin, with the geometry and initial temperatures acting as the physical asset. As the model was computed, the temperatures at specific points on the model were collected. The data was analyzed and compared to determine which recycled material best insulated the building. The fire-resistance properties, manufacturing process, and installation abilities should be researched in the future.

Graphical Abstract
Graphical abstract.

Click here to see my graphical abstract larger.

Click here to see my research proposal, grant proposal, and project notes.

Click here to see a draft of my thesis in an easier-to-read format.

Phrase 1 - If digital twin technology is utilized to determine the heat loss and insulation efficiency of various recycled insulation materials, homes can be kept warm while also reducing waste.

Phrase 2 - What recycled materials can be used as insulation to maintain inside temperatures while reducing waste?

Background
Background infographic.

Figure 1. Digitization index across industries (Abraham et al., 2019) .

Since ancient times, insulation has played an integral role in the way of human survival, as it aids at maintaining the temperature inside a building, which can prevent illness, allow for comfort, and in more modern times, save energy expenditure (Ringler, 2019). However, traditional insulations such as asbestos, fiberglass, foam, and cellulose can cause more harm than good to the humans that use them and to the environment they inhibit (Asbestos, 2021). Despite being a standard choice of insulation in the 1950’s, asbestos is highly dangerous and can cause many adverse health effects such as cancer. While the United States Environmental Protection Agency has attempted to ban asbestos, it is still legal to import, sell, and use asbestos (Asbestos Nation-EWG Action, n.d.). Additionally, the process of obtaining, using, and disposing of asbestos harms the environment. Mining of asbestos causes toxic particles to be released into the air, water, and soil (Asbestos, 2021). A similar release of asbestos particles places those who install and remove asbestos in danger as well (Wittmer, 2022). After asbestos is wetted or at the end of its use, it is placed in a specialty landfill, further contributing to pollution (MassDEP Asbestos, Construction and Demolition Notifications | Mass.Gov, n.d.). Manufacturers produce fiberglass, which contains fine glass fibers, in blankets, loose-fill, and boards (Insulation Materials, n.d.). While fiberglass is effective at maintaining building temperatures, the nature of its composition threatens humans who install and remove it; tiny glass fibers can be inhaled or touched and cause serious health issues (Why Traditional Home Insulation Is Bad for Your Health, 2017). Allowing for easy, spray installation, foam insulation is mainly used in harder to reach spaces such as attics, roofs, and lofts (UK Parliament, 2022). However, spray foam insulation causes worsened ventilation and additional condensation (UK Parliament, 2022). These two factors often cause wood around the spray foam insulation to decay (UK Parliament, 2022). Known as the most environmentally friendly insulation due to 80% of it being made from post-consumer recycled newsprint, cellulose insulation is excellent at maintaining temperatures and being flaim-resistant (Fisette, 2005). Due to the need for extensive maintenance, cellulose insulation often settles and allows for air movement and expansion into crevices where it is not wanted (Ringler, 2020). Despite having been mainly created from recycled materials, cellulose cannot be recycled due to it containing flame retardants (REenergizeCO, 2019). Overall, current insulations on the market cause consumers to have to weigh negative side-effects and environmental sustainability. This project aimed to utilize digital twin technology to determine an optimal recycled material to use as building insulation. This was achieved through the use of a type of Building Information Modeling called a Digital Twin to model the insulation’s efficiency and temperature distributions of differing recycled materials. In the United States, the construction industry is one of the least digitized industries (Abraham et al., 2019). Despite holding 13% of the world’s GDP, the construction industry has been slow to modernize (Construction Conundrum, n.d.). Existing technologies like Building Information Modeling (BIM) and growing Digital Twin (DT) technologies are essential to the digitization of the construction industry at large. Building Information Modeling is a representation of the construction, design, and operation phases of a building that is informed by data (André Borrmann, 2019). A way to connect Mechanical, Electrical, and Piping (MEP) systems to other structural aspects found in CAD, BIM technology allows for greater integration across various aspects of a project (Lester, 2014, p. 52). BIM technology allows construction projects to have a lifecycle approach, where not only architects, but engineers, construction managers, and facilities managers can utilize the BIM (Sinopoli, 2010, p. 13). BIM can simulate systems within the building such as HVAC, energy efficiency, and ventilation (Khan, 2021). This data can be used to inform decisions about what materials, designs, and systems should be used. Digital twins are a subset of building information modeling that is informed by real-world conditions (Pan et al., 2022). They are digital replicas of a physical asset that represent the current real-world conditions of the physical asset (Borrmann, 2019). The interconnectivity between the physical model and the simulated model allows for highly accurate modeling (Trauer et al., 2020). Digital twins can allow for not only the visualization of an exhaustive model, but also for the optimization of design. Although not widely adapted in the construction industry, digital twins have shown to be beneficial in the product development sector (Lin et al., 2021). When applied to the construction industry, digital twins are used in architectural and engineering processes as well as construction and facilities management. Software called COMSOL Multiphysics will be utilized to model the digital twin and perform physics-based model analysis on.

Proceedure infographic.

COMSOL Multiphysics modeling software, a finite element solver which can compute simulations, was used to model the wall and interior recycled material insulation. A two-dimensional temperature model was used. Through the geometry capabilities of COMSOL, a wall was constructed with basic measurements. For the purposes of this project, Pennsylvania State University's College of Earth and Mineral Sciences’ Composite Wall R-Values resource’s basic wall measurements was used to determine the measurements and materials of the geometry (Composite Wall R-Values | EGEE 102: Energy Conservation and Environmental Protection, n.d.). A large section filled with air accounted for the interior air temperature changes. Each part of the wall was defined with materials from the COMSOL materials library such that the region working as the insulation was included as a materials swap and further referenced as a materials sweep in the solving configurations. In addition, heat flux boundary conditions on the top and bottom of the wall allowed for more realistic modeling.

Plastic temperature distribution.

Figure 2. Surface temperature distribution graphic of recycled plastic generated in the COMSOL model.

Acrylic plastic temperature distribution.

Figure 3. Surface temperature distribution graphic of recycled acrylic plastic generated in the COMSOL model.

Paper temperature distribution.

Figure 4. Surface temperature distribution graphic of recycled paper generated in the COMSOL model.

Plastic temperature distribution.

Figure 5. Surface temperature distribution graphic of air generated in the COMSOL model.

CelluloseBoard temperature distribution.

Figure 6. Surface temperature distribution graphic of cellulose board generated in the COMSOL model.

Glass Wool Batt temperature distribution.

Figure 7. Surface temperature distribution graphic of glass wool batt generated in the COMSOL model.

Graph that compares the temperature and arc length of all of the materials tested.

Figure 8. An arc length temperature graph of independent and control group materials.

Analysis

Prior to modeling, materials data was collected via research. The density (kg/m^3), heat capacity at constant pressure (J/kgK), and thermal conductivity (W/(mK)) was collected for each material. The thermal conductivity was used to solve for overall thermal resistance of each material. The thermal resistance equation, R = xA k, was used, where R represents the overall thermal resistance, x represents the length of the material, A represents the cross sectional area, and k represents the thermal conductivity of the material. Due to the nature of the model, the cross sectional area was set to equal 1 square inch, as the depth of the wall has no importance on the purposes of this model. To determine the conduction heat transfer, Fourier’s Law of Heat Conduction was used such that q =T∞i-T∞1R, where q is the heat loss, T∞i is the warmer temperature, and T∞1 is the colder temperature. R and q were found for each of the materials in the independent and control groups. See figure 2 below. Data was collected through two means. First, the surface temperature was represented by color-coded surface temperature distributions created in COMSOL Multiphysics software, similarly to Figure 3. These were used as a basis of determining the overall efficacy of different materials. Given the key, blue meant lower temperatures, whereas red meant higher temperature. However due to the unquantifiable nature of these representations, they were only used for preliminary understanding. Each material was graphed in an arc length versus temperature graph. The arc length represents the displacement from the start of the geometry. This arc length was used to allow for the results to be interpreted for each section of the wall and further allow conclusions to be drawn based on where the slope of the line changed. To compare all of the materials, a single graph was created with both independent and control group materials (see Figure 4). Additionally, a graph that contained only the independent group materials and a graph that contained only the control group materials was created. This allowed for comparison of materials already known to be effective and materials that could be effective. Air was graphed on the control group graph. Porosity is not accounted for in the model. However, the graph that showed air helped to put into perspective how the addition of air with other effective materials might aid the effectiveness of the insulation. As for the independent group graph, the slope of the line for recycled aluminum is noticeably steeper than any other material. Recycled aluminum maintains a higher temperature within the insulation than any other material.

Table of materials values.

Figure 9. Table of the materials and their density, heat capacity at constant pressure, thermal conductivity, and length. The R-values and q values were determined based on these pieces of data and input temperatures.

Discussion and Conclusion

Based on the data collected in this research project, it can be concluded that all of this project’s objectives were accomplished. A digital twin was developed to model numerous recycled materials as insulation through the use of COMSOL. Simulations to determine how each material worked as insulation were completed. Conclusions can be drawn as to which recycled material works best as an insulation material based on the data collected. Limitations on this project included its redirection late into the project, new software being used in the final months of the project, and lack of knowledge in the software. When COMSOL was first implemented to model the insulation, most of the time spent on the project was used to learn COMSOL. Through research, mentorship, and numerous models being tried, the final model was created. This project found that materials that had the best insulation properties and abilities when the arc length was less than approximately 1.33 inches would have the worst insulation properties and abilities when the arc length was greater than approximately 1.33 inches. The inverse was found to be true as well. More specifically, air was a better insulation material when its arc length was less than 1.33 inches and worse when its arc length was greater than 1.33 inches. However, plastic was a better insulation material when its arc length was greater than 1.33 inches. Recycled aluminum was the best insulation material across the board. It maintained a higher temperature across the geometry with much less heat loss than all of the other materials. Further conclusions and research may draw one to suspect that air in combination with aluminum would be the best insulator out of those that were tested in this research.

References
February Fair Poster