Lifeboat Foundation: Safeguarding Humanity
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Category: nuclear energy

ABINGDON, England — Harnessing fusion energy into something commercially viable — and maybe, ultimately, a clean source of power that replaces fossil fuels for centuries to come — has long been considered by some as the ultimate moonshot.

But investor interest in fusion energy continues to slowly rise, and the number of startups in the field is multiplying, with an estimated 1,100 people in several countries making their living at these firms. An industry is taking shape, with a growing network of companies that supply highly specialized equipment, like the components of the powerful magnets that fusion devices require.

The British government even recently saw the need to issue regulations for fusion energy — a kind of milestone for a burgeoning industry.

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Nuclear energy is becoming more popular by the day and is being considered an eco-friendly option for the energy crisis we are going through. The US Department of Energy has dedicated US$20 million to a project that is based in Arizona that will use nuclear energy to make green hydrogen. They will be testing its capability as a liquid backup battery and as a secondary product for nuclear power installations.

The project will be headed by PNW Hydrogen LLC. They will build hydrogen production plants on-site at the Palo Verde Nuclear Generating Station in Phoenix, Arizona. Storage tanks will be used that will be able to store six tonnes of hydrogen onsite, representing about 200 MWh of energy that can be converted back into electricity and given to the grid when demand is more than usual.

The hydrogen will also be “used to make chemicals and other fuels,” and the project will gauge how nuclear stations can export and sell extra energy as an extra revenue stream. It is said that in the future, baseline power providers like nuclear stations will only be needed when the sun’s not shining or the wind’s not blowing. Hence, it makes sense to use this technology to make use of it and produce energy in the downtime.

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(2021). Nuclear Technology: Vol. 207 No. 8 pp. 1163–1181.

Focusing on nuclear engineering applications, the nation’s leading cybersecurity programs are focused on developing digital solutions to support reactor control for both on-site and remote operation. Many of the advanced reactor technologies currently under development by the nuclear industry, such as small modular reactors, microreactors, etc., require secure architectures for instrumentation, control, modeling, and simulation in order to meet their goals. 1 Thus, there is a strong need to develop communication solutions to enable secure function of advanced control strategies and to allow for an expanded use of data for operational decision making. This is important not only to avoid malicious attack scenarios focused on inflicting physical damage but also covert attacks designed to introduce minor process manipulation for economic gain. 2

These high-level goals necessitate many important functionalities, e.g., developing measures of trustworthiness of the code and simulation results against unauthorized access; developing measures of scientific confidence in the simulation results by carefully propagating and identifying dominant sources of uncertainties and by early detection of software crashes; and developing strategies to minimize the computational resources in terms of memory usage, storage requirements, and CPU time. By introducing these functionalities, the computers are subservient to the programmers. The existing predictive modeling philosophy has generally been reliant on the ability of the programmer to detect intrusion via specific instructions to tell the computer how to detect intrusion, keep log files to track code changes, limit access via perimeter defenses to ensure no unauthorized access, etc.

The last decade has witnessed a huge and impressive development of artificial intelligence (AI) algorithms in many scientific disciplines, which have promoted many computational scientists to explore how they can be embedded into predictive modeling applications. The reality, however, is that AI, premised since its inception on emulating human intelligence, is still very far from realizing its goal. Any human-emulating intelligence must be able to achieve two key tasks: the ability to store experiences and the ability to recall and process these experiences at will. Many of the existing AI advances have primarily focused on the latter goal and have accomplished efficient and intelligent data processing. Researchers on adversarial AI have shown over the past decade that any AI technique could be misled if presented with the wrong data. 3 Hence, this paper focuses on introducing a novel predictive paradigm, referred to as covert cognizance, or C2 for short, designed to enable predictive models to develop a secure incorruptible memory of their execution, representing the first key requirement for a human-emulating intelligence. This memory, or self-cognizance, is key for a predictive model to be effective and resilient in both adversarial and nonadversarial settings. In our context, “memory” does not imply the dynamic or static memory allocated for a software execution; instead, it is a collective record of all its execution characteristics, including run-time information, the output generated in each run, the local variables rendered by each subroutine, etc.

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(2021). Nuclear Science and Engineering: Vol. 195 No. 9 pp. 977–989.

Earlier work has demonstrated the theoretical development of covert OT defenses and their application to representative control problems in a nuclear reactor. Given their ability to store information in the system nonobservable space using one-time-pad randomization techniques, the new C2 modeling paradigm6 has emerged allowing the system to build memory or self-awareness about its past and current state. The idea is to store information using randomized mathematical operators about one system subcomponent, e.g., the reactor core inlet and exit temperature, into the nonobservable space of another subcomponent, e.g., the water level in a steam generator, creating an incorruptible record of the system state. If the attackers attempt to falsify the sensor data in an attempt to send the system along an undesirable trajectory, they will have to learn all the inserted signatures across the various system subcomponents and the C2 embedding process.

We posit that this is extremely unlikely given the huge size of the nonobservable space for most complex systems, and the use of randomized techniques for signature insertion, rendering a level of security that matches the Vernam-Cipher gold standard. The Vernam Cipher, commonly known as a one-time pad, is a cipher that encrypts a message using a random key (pad) and can only be decrypted using this key. Its strength is derived from Shannon’s notion of perfect secrecy 8 and requires the key to be truly random and nonreusable (one time). To demonstrate this, this paper will validate the implementation of C2 using sophisticated AI tools such as long short-term memory (LSTM) neural networks 9 and the generative adversarial learning [generative adversarial networks (GANs)] framework, 10 both using a supervised learning setting, i.e., by assuming that the AI training phase can distinguish between original data and the data containing the embedded signatures. While this is an unlikely scenario, it is assumed to demonstrate the resilience of the C2 signatures to discovery by AI techniques.

The paper is organized as follows. Section II provides a brief summary of existing passive and active OT defenses against various types of data deception attacks, followed by an overview of the C2 modeling paradigm in Sec. III. Section IV formulates the problem statement of the C2 implementation in a generalized control system and identifies the key criteria of zero impact and zero observability. Section V implements a rendition of the C2 approach in a representative nuclear reactor model and highlights the goal of the paper, i.e., to validate the implementation using sophisticated AI tools. It also provides a rationale behind the chosen AI framework. Last, Sec. VI summarizes the validation results of the C2 implementation and discusses several extensions to the work.

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Nuclear power is going portable in the form of relatively lightweight, cost-effective microreactors. A team of former SpaceX engineers is developing the “world’s first portable, zero-emissions power source” that can bring power to remote areas and also allows for quick installation of new units in populated areas, a press statement revealed.

Last year, the team secured $1.2 million in funding from angel investors for their startup Radiant to help develop its portable nuclear microreactors, which are aimed at both commercial and military applications.

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Could combining solar panels plus farming be a viable solution to the growing demand for food production and energy demand? Let’s take a closer look at electrifying our crops (not literally electrifying crops) … well, adding solar to our farm land as well as some of the side benefits and challenges it creates.

Watch 28,000 Year Nuclear Waste Battery? Diamond Batteries Explained.

Video script and citations:
https://undecidedmf.com/episodes/solar-panels-plus-farming-agrivoltaics-explained.

Follow-up podcast:
Video version — https://www.youtube.com/channel/UC4-aWB84Bupf5hxGqrwYqLA
Audio version — http://bit.ly/stilltbdfm.

Special thanks to BayWa and GroenLeven for some of the video footage and photography.
https://www.baywa-re.com.
https://groenleven.nl/

👋 Support Undecided on Patreon!
https://www.patreon.com/mattferrell.

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It sounds like a scene from a spy thriller. An attacker gets through the IT defenses of a nuclear power plant and feeds it fake, realistic data, tricking its computer systems and personnel into thinking operations are normal. The attacker then disrupts the function of key plant machinery, causing it to misperform or break down. By the time system operators realize they’ve been duped, it’s too late, with catastrophic results.

The scenario isn’t fictional; it happened in 2,010 when the Stuxnet virus was used to damage nuclear centrifuges in Iran. And as ransomware and other cyberattacks around the world increase, system operators worry more about these sophisticated “false data injection” strikes. In the wrong hands, the computer models and data analytics—based on artificial intelligence—that ensure smooth operation of today’s electric grids, manufacturing facilities, and power plants could be turned against themselves.

Purdue University’s Hany Abdel-Khalik has come up with a powerful response: To make the computer models that run these cyberphysical systems both self-aware and self-healing. Using the background noise within these systems’ data streams, Abdel-Khalik and his students embed invisible, ever-changing, one-time-use signals that turn passive components into active watchers. Even if an is armed with a perfect duplicate of a system’s model, any attempt to introduce falsified data will be immediately detected and rejected by the system itself, requiring no human response.

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“The twisted coils are the most expensive and complicated part of the stellarator and have to be manufactured to very great precision in a very complicated form,” physicist Per Helander, head of the Stellarator Theory Division at Max Planck and lead author of the new paper, told Princeton Plasma Physics Laboratory News.

The new design offers a simpler approach by instead using permanent magnets, whose magnetic field is generated by the internal structure of the material itself. As described in an article published by Nature, Zarnstorff realized that neodymium–boron permanent magnets—which behave like refrigerator magnets, only stronger—had become powerful enough to potentially help control the plasma in stellarators.

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Advanced Nuclear Power Advocacy For Humanity — Eric G. Meyer, Founder & Director, Generation Atomic

Eric G. Meyer is the Founder and Director of Generation Atomic (https://generationatomic.org/), a nuclear advocacy non-profit which he founded after hearing about the promise of advanced nuclear reactors, and he decided to devote his life to saving and expanding the use of atomic energy.

Eric worked as an organizer on several political, union, and issue campaigns while in graduate school for applied public policy, taking time off to attend the climate talks in Paris and sing opera about atomic energy.

Eric began his full time nuclear work in May of 2016 with Environmental Progress by organizing marches, rallies, and trainings in California, New York, and Illinois, before leaving to found Generation Atomic in late 2016.

In only a short period of time, Generation Atomic has made significant progress in the world of nuclear advocacy. Over the last year they’ve held several advocacy trainings at conferences, Marched for Science, talked to over tens of thousands voters, and carried the banner for nuclear energy at the climate talks in Morocco, Germany, and Poland.

Eric attended University of Minnesota-Duluth where he obtained a Master’s Degree in Advocacy and Political Leadership, with Concentrations in Public Sector and Non-profits, and a Bachelor of Arts in Music Performance.

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