In recent years, the trend in small modular reactor (SMR) technology development has been towards the water-cooled integral pressurized water reactor (iPWR) type. The innovative and unique characteristics of iPWR-type SMRs provide an enhanced safety margin, and thus offer the potential to expand the use of safe, clean, and reliable nuclear energy to a broad range of energy applications. Currently in the world, there are about eleven (11) iPWR-type SMRs concepts and designs that are in various phases of development: under construction, licensed or in the licensing review process, the development phase, and conceptual design phase. Lack of national and/or internatonal comparative framework for safety in SMR design, as well as the proprietary nature of designs introduces non-uniformity and uncertainties in regulatory review. That said, the major primary reactor coolant system components, such as the steam generator (SG), pressurizer (PRZ), and control rod drive mechanism (CRDM) are integrated within the reactor pressure vessel (RPV) to inherently eliminate or minimize potential accident initiators, such as LB-loss of coolant accidents (LOCAs). This paper presents the design status, innovative features and characteristics of iPWR-type SMRs. We delineate the common technology trends, and highlight the key features of each design. These reactor concepts exploit natural physical laws such as gravity to achieve the safety functions with high level of margin and reliability. In fact, many SMR designs employ passive safety systems (PSS) to meet the evolving stringent regulatory requirements, and the extended consideration for severe accidents. A generic classification of PSS is provided. We constrain our discussion to the decay heat removal system, safety injection system, reactor depressurization system, and containment system. A review and comparative assessment of these passive features in each iPWR-type SMR design is considered, and we underline how it maybe more advantageous to employ passive systems in SMRs in contrast to conventional reactor designs.

To meet climate policy goals, it will be necessary to deploy a series of low-carbon energy technologies, including nuclear power. The small modular reactor (SMR) can potentially support climate change mitigation and energy security issues. Small modular reactors (SMRs) are gaining popularity; however, one crucial debate is whether SMRs can compete economically with conventional nuclear reactors or not. From a commercial point of view, SMRs will be able to provide process heat in various industrial applications, replace older nuclear, natural gas, and coal power facilities, and serve smaller energy markets with less established infrastructure. Realizing these advantages would rely heavily on the near-term quick up-scaling of SMRs; this paper, then, examines and identifies some of the most hindering constraints and barriers for the quick deployment of SMR such as the technology choice, licensing, economy of scale and financing, public acceptance, supply chain, and proliferation. A clear identification of the evident and more hidden bottlenecks preventing a quick deployment is made putting in evidence areas in need of much deeper analysis than the one conducted by the SMR community so far.

During the last few years, nuclear energy has received great attention due to the increase in climate change awareness. According to the Paris agreement, global temperature is to be kept below 2 °C and preferably below 1.5 °C by 2050. This approach has been substantially confirmed in the recent COP 26 in Glasgow. This research investigates the effects of integrating SMR nuclear power plants (small modular reactors) into the Nordhaus Dynamic Integrated Climate Economy (DICE) model for reducing the CO₂ emissions in the atmosphere by substituting all existing fossil-fueled power plants (FPPP). The software is based on the VENSIM dynamic systems modeling platform. Simulations were carried out from the year 2019 to 2100 using 10-year increments. Several scenarios were thus simulated replacing roughly 70,000 FPPPs operating at this time in the world. Simulations indicate a CO₂ reduction of approximately 12.63% relative to the initial conditions used and using 87,830 SMR core units of 80 MWe electric each to meet such demand. The DICE model further predicts the cost of climate damage impacting the upper ocean and atmospheric temperatures, and the deep ocean temperature as USD 1.515 trillion (US Dollar; (US) trillion = 1,000,000,000,000 (1 × 10¹²)) by the end of this century. From a modified section of the model, a cost of USD 1.073 trillion is predicted as the toll on human health costs. This is thus equal to a USD 2.59 trillion loss in the economy.

In response to the urgent threat of climate change and the drivers of high greenhouse gas emissions, countries worldwide are adopting policies to reduce their carbon emissions, with net-zero emissions targets. These targets vary by region, with Canada aiming to achieve net-zero emissions by 2050. In response to the Independent Electricity System Operator’s (IESO’s) “Pathways to Decarbonization” report, which evaluates a proposed moratorium on new natural gas generating stations, this study presents a methodology to support energy transitions in Ontario by using a modified Dynamic Integrated Climate-Economy (DICE) model, which focuses on replacing fossil fuel power plants (FFPPs) with clean energy sources, including nuclear, solar, wind, and hydro. This research expands on our prior work that used the DICE model to evaluate the potential for replacing FFPPs with Small Modular Reactors (SMRs) on a global scale. This study includes solar, wind, hydro, and SMRs to provide a diversified clean energy portfolio and integrates fuzzy logic to optimize construction rates and address uncertainties. The study uses Ontario as a case study, aligning with IESO’s objectives for Ontario’s energy transition. The IESO’s projections for net zero by 2050 are applied. The study is extended to 2100 to assess the longer-term implications of sustained energy transition efforts beyond the immediate goals set by the IESO. This approach is scalable to other regions and countries with similar energy transition challenges. The study results indicate that to meet Ontario’s 2050 net-zero target, approximately 183 SMR units, 1527 solar units, 289 wind units, and 449 hydro units need to be constructed. For the 2100 target, the required number of units is slightly higher due to the longer time frame, reflecting a gradual ramp-up in construction. The optimization of construction rates using fuzzy logic shows that the pace of deployment is influenced by critical factors such as resource availability, policy support, and public acceptance. This underscores the need for accelerated clean energy deployment to meet long-term emissions reduction goals. The findings highlight the complexities of transitioning to a low-carbon energy system and the importance of addressing uncertainties in planning. Policymakers are urged to integrate these insights into strategic energy planning to ensure the successful deployment of clean energy technologies. This study provides valuable recommendations for optimizing energy transitions through a robust, flexible framework that accounts for both technological and socio-economic challenges.

This study addresses the urgent need for transitioning to clean energy systems to achieve net-zero emissions and mitigate climate change. It introduces an algebraic modeling framework inspired by the nuclear fission six-factor formula to optimize the construction rates of clean power plants, with a focus on Small Modular Reactors (SMRs). The framework integrates four key factors affecting SMR deployment: Public Acceptance (PA), Supply Chain Readiness (SC), Human Resource (HR) Availability, and Land Availability (LA), including their associated sub-factors. The proposed algebraic formula optimizes projections from the existing Dynamic Integrated Climate-Economy (DICE) model. By capturing socio-economic and environmental constraints, the model enhances the accuracy of clean energy transition scenarios. In the case of Ontario’s pathway to achieving net-zero emissions, the results indicate that incorporating the algebraic formula reduces the SMR construction rate projected by the DICE model from 5.2 to 3.7 units per year by 2050 and from 2.7 to 1.9 units per year by 2100. This reduction highlights the need for accelerated readiness in key deployment factors to avoid delays in reaching net zero targets, reinforcing the importance of strategic investments in PA, SC, HR, and LA. Validation against historical nuclear deployment data from the U.S., Japan, and Canada confirms the model’s ability to reflect real-world trends, with PA and SC emerging as the most influential factors. In addition to informing SMR planning, this approach offers a structured tool for prioritizing policy actions and can be adapted to other clean technologies, enhancing strategic decision making in support of net-zero goals.