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Joshua Pearce is a cross-appointed Professor at the Ivey and the Department of Electrical & Computer Engineering. He is the John M. Thompson Chair in Information Technology and Innovation at the Thompson Centre for Engineering Leadership & Innovation. His research spans areas of solar photovoltaic technology, open hardware, distributed recycling and additive manufacturing, policy and economics.
Joshua runs the Free Appropriate Sustainability Technology (FAST) research group. He has worked with, consulted for, and been funded by dozens of renewable energy and additive manufacturing companies as well as the US Government and the UN.
His research was the first to show that levelized cost of solar photovoltaic electricity was economically competitive in North America, the first to demonstrate that open hardware can save scientists 90-99% on research costs, and the first to show that household level distributed recycling and manufacturing were technically feasible, less environmentally harmful and profitable for consumers. His research is regularly covered by the international and national press and it is continually ranked in the top 0.1% on Academia.edu. He is the editor-in-chief of HardwareX, the first journal dedicated to open source scientific hardware and the author of the Open-Source Lab:How to Build Your Own Hardware and Reduce Research Costs, Create, Share, and Save Money Using Open-Source Projects, and To Catch the Sun, an open source book on how to harness solar energy.
Joshua Pearce received his Ph.D. in Materials Engineering from the Pennsylvania State University. He then developed the first Sustainability program in the Pennsylvania State System of Higher Education and helped develop the Collaborative Applied Sustainability graduate engineering program while at Queen's University, Canada. Then he was the first Richard Witte Professor of Materials Science and Engineering and a Professor cross-appointed in the Department of Electrical & Computer Engineering at the Michigan Technological University where he inaugurated and was the faculty advisor for the Michigan Tech Open Source Hardware Enterprise and ran the Open Sustainability Technology Research Group. He was a Fulbright-Aalto University Distinguished Chair and a visiting professor of Photovoltaics and Nanoengineering at Aalto University as well as a visiting Professor Équipe de Recherche sur les Processus Innovatifs (ERPI), Université de Lorraine, France.
Dr. Pearce is always looking for motivated research students and collaborators. See here.
Abstract: Greenhouses play a crucial role in food production and economic growth in northern regions but contribute significantly to energy consumption and carbon emissions. To address this challenge and enhance food production sustainably, there is a growing need for efficient and renewable energy solutions. Low-carbon heating in greenhouses will be achievable by using heat pumps powered by cost-effective renewable energy sources such as photovoltaic systems. This study introduces an open-source quasi-steady-state thermal model for greenhouses, non-ideal air-source heat pumps (ASHPs), and ground-source heat pumps (GSHPs) with both vertical (V) and horizontal (H) ground heat exchangers. Additionally, a ventilation sub-model is provided to manage cooling loads for residential, semi-commercial, and commercial greenhouses. Furthermore, an open-source SAM-Python-based photovoltaic system model is developed to size photovoltaic arrays for powering the heat pumps. The study reveals a nonlinear relationship between greenhouse size and annual thermal loads. It also demonstrates that ASHPs exhibit the lowest efficiency (COPh = 2.52, EERc = 9.00), followed by VGSHPs (COPh = 3.68, EERc = 19.88), with HGSHPs being the most efficient (COPh = 3.79, EERc = 19.48) for the Canadian case study. The required on-grid photovoltaic ratings to power HGSHPs, VGSHPs, and ASHPs respectively are 2.16, 2.17, and 2.64 kW for residential, 103, 104, and 128 kW for semi-commercial, and 827, 831, and 1,028 kW for commercial greenhouses. Self-consumption of designed photovoltaic systems ranges from 23.5 % to 25.1 %, with self-sufficiency varying between 23.7 % and 26.0 %. The size of the photovoltaic system is competitive with similar scenarios; however, future studies are needed to conduct an economic analysis while simulating the dynamic loads of greenhouses.
Abstract: Comprehensive water quality control is a fundamental requirement for environmental preservation and the sustainable development of communities around the globe. To showcase the importance of local quality controls in identifying the sources of pollution, a case study was conducted to analyze the quality of drinking water from different locations along the Cauvery River from Mettur to Trichy (200 km) in Tamil Nadu, India. The quality of water samples from different locations was indexed and compared with the World Health Organization and Indian Standards of water quality. The results indicate some high local values of TDS, hardness, and chloride content. These high values may be due to effluents from industries, dying factories, and sewage from the urban areas on the banks of the Cauvery River. This is most prevalent near Mohanur, where industrial waste and effluents were directly linked into the river. The results emphasize the importance of local quality control for accurately pinpointing the factors affecting the environment.
Abstract: Fully sustainable hydrogen production demands renewable energy sources. This study uses an approach that combines solar photovoltaic (PV) systems with batteries to tailor the energy supply to the unique demands of anion exchange membrane (AEM) electrolyzers. An open source DC-DC adjustable converter is designed, prototyped, and tested to enable an AEM to operate at its optimum efficiency without disrupting the continuous operation of existing loads. A structured operating schedule is simulated to align PV performance with AEM electrolyzer characteristics. The results show the >90% efficiency open-source converter was able to directly power the electrolyzer while taking advantage of solar energy surplus for hydrogen production. By strategically scheduling the electrolyzer to maximize output and minimize waste the system only utilizes excess solar energy. By employing this sustainable method, the study highlights a scalable solution that not only enhances the efficiency of hydrogen production, but also promotes the deployment of PV.
Abstract: Agrivoltaic agrotunnels are currently designed for high-density grow walls that are not amenable to bush berries or root crops. Commercial grow bins provide deeper substrates for produce with more root systems but have high costs per unit growing area. To overcome the economic limitations of grow bins, this study applies the distributed manufacturing open-source design paradigm to develop four designs for low-cost open-source structures. The designs target root vegetables and bush fruit specifically to be adopted by remote communities with limited or no outdoor growing environment to offset the market price for imported fresh produce. The indoor growing designs provide the necessary structure for supporting grow lights and grow bins and enable the transplanted berry plants to flower and produce fruits. They provide a comparable amount (110 L) or more of grow volume from 106 to 192 L. The water reservoir volume for the commercial system (62 L) and grow area (0.5 m3) is surpassed by all new designs that range from 64 to 192 L and 0.51 to 0.76 m3, respectively. These superior properties are possible with material costs for all four designs that save more than 90% of the economic cost of the commercial systems.
Abstract: Canada can radically reduce greenhouse gas (GHG) emissions by aggressively deploying agrivoltaics and reach its goal of cutting emissions by increasing the non-emitting share of electricity generation to 90 % by 2030. To help reach this goal, this study evaluated the potential energy production for vertical bi-facial solar photovoltaic arrays as well as the solar irradiation reaching the ground with three different spacings (5 m, 15 m and 45 m) and three different Canadian farming locations (London, Calgary and Winnipeg) using irradiance modeling with Ladybug tools plug-ins for Grasshopper and Honeybee. The crops currently grown in each region were identified and their sunlight requirements were analyzed. Based on the amount of solar radiation reaching the ground surface and the solar requirements of the crops, inter-row spacings that were suitable for agrivoltaic applications for the three locations were identified. Next the land acreage of a select few crops, which were proven to be satisfactory for agrivoltaic systems, were identified for each province and their electrical energy potential was ascertained using the open-source System Advisor Model. The results indicate that more than 84 % of the total national electricity requirements can be met by employing agrivoltaics on agricultural land where these crops are cultivated in the three provinces.
Abstract: To produce samples for both material testing and molded sheets/parts, this article details an open-source scientific cold and hot press design. It consists of two independent and modular upper and lower plate (929 cm2) assemblies each containing four 125 W insulated steel strip heaters. The steel housing for these heaters is entirely modular and designed for ease of manufacture, assembly, and customization. This system allows a researcher with access to a hydraulic press to repurpose existing equipment into a multipurpose hot and cold press, or if an independent machine is warranted, an additional welded support frame and commercially available bottle jack offer standalone operation. By utilizing this small-scale hot press either in conjunction with a hydraulic press or on its own, samples can be produced to determine the critical material properties of any polymer, composite, or polymer blend. A series of modular molds allow for the rapid production of flat sheet stock and solid testing samples adhering to the ASTM D695 standard for rigid plastics tested in compression and ASTM D638 standard for testing plastics in tension. The sheet mold offers the user the ability to produce stock sheets that can be cut and assembled into 2.5-D applications with post processing.
Abstract: The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids is well established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge, which results in high costs. To enable a democratization of the technology by reducing the costs, this study provides a novel modular plug-and-play open-source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink (version 2024b) as well as experimental validation. The results show that transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network, as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.
Abstract: Solar photovoltaic (PV) wood-based rack designs support distributed manufacturing, have lifetimes equivalent to PV warranties, have lower embodied energy and carbon emissions and cost less than conventional racking. Unfortunately, wood racking does not enable the standard front surface attachments. To overcome this challenge this study introduces novel 3D printed clamps for front-surface PV mounting on wood racking. Four topologies (square spacer, H-shaped spacer, U-shaped clamp and T-shaped clamp) of 3D printed parts are designed, modelled and analyzed using finite element analysis for PETG, ASA and PC. The designs were fabricated, field tested and economically analyzed. The highest stress was observed in U-shaped spacer for spacer (4.53 MPa – PC material), bolt (32.01 MPa – PETG material) and frame (37.30 MPa) and for washer in the H-spacer (42.77 MPa). Mises stresses for all designs, however, are found within allowable limits qualifying the clamping technique to be adopted for future installations. Financial analysis of the clamps found up to 66% savings for the solutions. The T-shaped clamp is the recommended mounting technique with the lowest stresses while square spacer provides the least cost. The practical implications of the results indicate that 3D printing could provide an economic means of mounting PV modules and reducing solar energy costs.
Abstract: Local indoor farming plays a significant role in the sustainable food production sector. The operation and energy costs, however, have led to bankruptcy and difficulties in cost management of indoor farming operations. To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: (1) high insulation for a building dedicated to vertical growing, (2) high-efficiency light emitting diode (LED) lighting, (3) heat pumps (HPs), and (4) solar photovoltaics (PVs) to provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plant evapotranspiration can be included. HPs are sized and plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50 kW and make up an area from 3.2 to 10.48 m2/m2 of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.
Abstract: Machine learning and computer vision have proven to be valuable tools for farmers to streamline their resource utilization to lead to more sustainable and efficient agricultural production. These techniques have been applied to strawberry cultivation in the past with limited success. To build on this past work, in this study, two separate sets of strawberry images, along with their associated diseases, were collected and subjected to resizing and augmentation. Subsequently, a combined dataset consisting of nine classes was utilized to fine-tune three distinct pretrained models: vision transformer (ViT), MobileNetV2, and ResNet18. To address the imbalanced class distribution in the dataset, each class was assigned weights to ensure nearly equal impact during the training process. To enhance the outcomes, new images were generated by removing backgrounds, reducing noise, and flipping them. The performances of ViT, MobileNetV2, and ResNet18 were compared after being selected. Customization specific to the task was applied to all three algorithms, and their performances were assessed. Throughout this experiment, none of the layers were frozen, ensuring all layers remained active during training. Attention heads were incorporated into the first five and last five layers of MobileNetV2 and ResNet18, while the architecture of ViT was modified. The results indicated accuracy factors of 98.4%, 98.1%, and 97.9% for ViT, MobileNetV2, and ResNet18, respectively. Despite the data being imbalanced, the precision, which indicates the proportion of correctly identified positive instances among all predicted positive instances, approached nearly 99% with the ViT. MobileNetV2 and ResNet18 demonstrated similar results. Overall, the analysis revealed that the vision transformer model exhibited superior performance in strawberry ripeness and disease classification. The inclusion of attention heads in the early layers of ResNet18 and MobileNet18, along with the inherent attention mechanism in ViT, improved the accuracy of image identification. These findings offer the potential for farmers to enhance strawberry cultivation through passive camera monitoring alone, promoting the health and well-being of the population.
Abstract: To enable net zero sustainable thermal building energy, this study develops an open-source thermal house model to couple solar photovoltaic (PV) and heat pumps (HPs) for grid-connected residential housing. The calculation of both space heating and cooling thermal loads and the selection of HP is accomplished with a validated Python model for air-source heat pumps. The capacity of PV required to supply the HPs is calculated using a System Advisor Model integrated Python model. Self-sufficiency and self-consumption of PV and the energy imported/exported to the grid for a case study are provided, which shows that simulations based on the monthly load profile have a significant reduction of 43% for energy sent to/from the grid compared to the detailed hourly simulation and an increase from 30% to 60% for self-consumption and self-sufficiency. These results show the importance of more granular modeling and also indicate mismatches of PV generation and HP load based on hourly simulation datasets. The back-calculation PV sizing algorithm combined with HP and thermal loads presented in this study exhibited robust performance. The results indicate this approach can be used to accelerate the solar electrification of heating and cooling to offset the use of fossil fuels in northern climates.
Abstract: A variety of events such as high-altitude electromagnetic pulses, extreme solar storms, and coordinated cyber attacks could result in a catastrophic loss of infrastructure on a continental or global scale. The lengthy repair of critical infrastructure creates a need for alternative fuels such as wood gas. Wood gas is produced by heating wood in a low-oxygen environment and can be used to power combustion engines. This work investigates a novel wood chipper, designed as an energy-efficient tool for producing wood gas stock, wood chips, aiming to speed up the transition to alternative fuel. A prototype is built and tested to determine the energy efficiency and production rate of the device. The results suggest that the wood chipper could produce one cord of wood chips, 3.6 m3, in less than a day and is a viable alternative to other manual wood-processing methods. In addition, the global scaling up of production of the wood chipper is considered, indicating that the mass production of the wood chipper could accelerate the transition of wood gas production methods from manual to machine-driven immediately after a catastrophic event.
Abstract: The high volume of plastic waste and the extremely low recycling rate have created a serious challenge worldwide. Local distributed recycling and additive manufacturing (DRAM) offers a solution by economically incentivizing local recycling. One DRAM technology capable of processing large quantities of plastic waste is fused granular fabrication, where solid shredded plastic waste can be reused directly as 3D printing feedstock. This study presents an experimental assessment of multi-material recycling printability using two of the most common thermoplastics in the beverage industry, polyethylene terephthalate (PET) and high-density polyethylene (HDPE), and the feasibility of mixing PET and HDPE to be used as a feedstock material for large-scale 3-D printing. After the material collection, shredding, and cleaning, the characterization and optimization of parameters for 3D printing were performed. Results showed the feasibility of printing a large object from rPET/rHDPE flakes, reducing production costs by up to 88%.
Abstract: The application of computer vision and machine learning methods for semantic segmentation of the structural elements of 3D-printed products in the field of additive manufacturing (AM) can improve real-time failure analysis systems and potentially reduce the number of defects by providing additional tools for in situ corrections. This work demonstrates the possibilities of using physics-based rendering for labeled image dataset generation, as well as image-to-image style transfer capabilities to improve the accuracy of real image segmentation for AM systems. Multi-class semantic segmentation experiments were carried out based on the U-Net model and the cycle generative adversarial network. The test results demonstrated the capacity of this method to detect such structural elements of 3D-printed parts as a top (last printed) layer, infill, shell, and support. A basis for further segmentation system enhancement by utilizing image-to-image style transfer and domain adaptation technologies was also considered. The results indicate that using style transfer as a precursor to domain adaptation can improve real 3D printing image segmentation in situations where a model trained on synthetic data is the only tool available. The mean intersection over union (mIoU) scores for synthetic test datasets included 94.90% for the entire 3D-printed part, 73.33% for the top layer, 78.93% for the infill, 55.31% for the shell, and 69.45% for supports.
Abstract: Open-source design of medical devices, following the concept of frugal engineering, provides unrestricted descriptions of technical details, allowing the low-cost and local fabrication of devices to reduce global inequities in healthcare.
