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Practical applications of model checking in the finnish nuclear industry - 281

Model checking is a powerful, formal, computer-assisted verification method that can be used to prove that a model of a (hardware or software) system fulfills stated properties. When used right, model checking can prove the correctness of instrumentation and control (I and C) system application logic, be it a software or a field-programmable gate array (FPGA) based design. The verified properties can also address unwanted functionality, making model checking a very effective method for analyzing spurious actuation. Despite the benefits, model checking is still not widely adopted in the verification of I and C systems, one exception being the Finnish nuclear industry. Since 2008, VTT has applied model checking in practical customer work related to the Olkiluoto 3 EPR, Loviisa 1 and 2 VVER-440, and Hanhikivi 1 AES-2006 nuclear power plants, on commission from either the regulator or the utilities. In this paper, we look at how the method has been used in each of these three projects. We also introduce a user-friendly, graphical modelling tool called MODCHK. We then present an overall view of the design issues detected during nine years of customer work, and one practical example. The 100% coverage means that the design errors that are found often relate to scenarios that are otherwise hard to account for (e.g., exact timing of events, or improper operator actions). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Applying Incremental, Inductive Model Checking to the Modal Mu Calculus

This work aims to demonstrate that an incremental inductive model checking algorithm built on top of Boolean satisfiability (SAT) solvers can be extended to support modal mu calculus (MMC) formulas. The resulting algorithm, called modal mu calculus model checking using myopic constraints (MC3), solves MMC model checking problems over Boolean labeled transition systems (LTSs). MMC subsumes simple invariance/reachability (as solved by the IC3 algorithm), linear temporal logic (LTL, as solved by the fair algorithm), computation tree logic (CTL, as solved by IICTL), and CTL* (which in turn subsumes LTL and CTL, but was not previously supported by any incremental inductive algorithm). The algorithm is implemented in a prototype solver, mc3.

97 MATHEMATICS AND COMPUTING↗

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Systematic Approach to Offshore Wind Turbine Jacket Pre-Design and Optimization: Geometry, Cost, and Surrogate Structural Code Check Models

The main obstacles in preliminary design studies or optimization of jacket substructures for offshore wind turbines are high numerical expenses for structural code checks and simplistic cost assumptions. In order to create a basis for fast design evaluations, this article provides the following: firstly, a jacket model is proposed that covers topology and tube sizing with a limited set of design variables. Secondly, a cost model is proposed that goes beyond the simple and common mass-dependent approach. And thirdly, the issue of numerical efficiency is addressed by surrogate models both for fatigue and ultimate limit state code checks. In addition, this work shows an example utilizing all models. The outcome can be utilized for preliminary design studies and jacket optimization schemes and is suitable for scientific and industrial applications.

17 WIND ENERGY↗

Emulation automation and model checking

A method of automating emulations is provided. The method comprising collecting publicly available network data over a predefined time interval, wherein the collected network data might comprise structured and unstructured data. Any unstructured data is converted into structured data. The original and converted structured data is stored in a database and compared to known network vulnerabilities. An emulated network is created according to the collected network data and the comparison of the structured data with known vulnerabilities. Virtual machines are created to run on the emulated network. Director programs and guest actor programs are run on the virtual machines, wherein the actor programs imitate real user behavior on the emulated network. The director programs deliver task commands to the guest actor programs to imitate real user behavior. The imitated behavior is presented to a user via an interface.

Urias, Vincent↗

OpenStudio® Standards [SWR-07-40]

OpenStudio® Standards is a Ruby Gem library that extends the OpenStudio SDK. It has four main use-cases: Provide higher level methods to help BEM users and developers to create OpenStudio models from existing geometry, or programmatically generated geometry Create typical building models in OpenStudio format Create a code baseline model from a proposed model Check a model against a code/standard openstudio-standards previously supported making the DOE/PNNL prototype buildings in OpenStudio format. This has since been deprecated, as the DOE/PNNL prototypes are intended for specific code comparisons under the Energy Policy Act and are not intended to accurately represent typical existing or new buildings. While openstudio-standards still creates typical buildings, these are not the same as the DOE/PNNL prototypes.

Lopez, Phylroy↗

Subsidence Infiltration Model Design Check for E-Area LLWF

A design check will be performed on the revised Python-based probabilistic subsidence infiltration model for the proposed E-Area Low-Level Waste Facility (LLWF) final closure cap design.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Intact Infiltration Model Design Check for E-Area LLWF

A design check will be performed on the infiltration-rate time profile for the intact case for the proposed E-Area Low-Level Waste Facility (LLWF) final closure cap design.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗

On the Power of Uncertainties in Microbial System Modeling: No Need To Hide Them Anymore

For decades, microbiologists have considered uncertainties as an undesired side effect of experimental protocols. As a consequence, standard microbial system modeling strives to hide uncertainties for the sake of deterministic understanding. However, recent studies have highlighted greater experimental variability than expected and emphasized uncertainties not as a weakness but as a necessary feature of complex microbial systems. We therefore advocate that biological uncertainties need to be considered foundational facets that must be incorporated in models. Not only will understanding these uncertainties improve our understanding and identification of microbial traits, it will also provide fundamental insights on microbial systems as a whole. Taking into account uncertainties within microbial models calls for new validation techniques. Formal verification already overcomes this shortcoming by proposing modeling frameworks and validation techniques dedicated to probabilistic models. However, further work remains to extract the full potential of such techniques in the context of microbial models. Herein, we demonstrate how statistical model checking can enhance the development of microbial models by building confidence in the estimation of critical parameters and through improved sensitivity analyses.

59 BASIC BIOLOGICAL SCIENCES↗

Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those new security components into different groups according to their purpose and deployment scope. We propose to analyze them in the context of existing 5G architectures using two different approaches. First, using model checking techniques, we will evaluate the probability of an attacker to be successful against each security solution. Second, using analytical models, we will analyze the impact of these security mechanisms in terms of delay, throughput consumption, and reliability. Finally, we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture. Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced, dedicated non-native mechanisms could only guarantee secure URLLC with a probability of ~55%.

5G networks↗

Improving Deployment Availability of Energy Storage With Data-Driven AGC Signal Models

Energy Storage (ES) provides great flexibility and large benefits to power system operations and control. When providing ancillary services (e.g., regulation, reserve, etc.), the real-time (RT) deployment of ES is uncertain, and it is important to manage state of charge accordingly. Aiming to improve the ES performance for providing energy and regulation service in the electricity market, we propose two data-driven Automatic Generation Control (AGC) signal models. The first one is a historical-data-driven AGC signal model, which is based on the analysis of the historical AGC signals, and is designed for ES participation in the day-ahead (DA) market. The second one is a prediction-data-driven AGC signal model, which is based on the prediction of the AGC signals, and is designed for ES participation in the RT market. We also develop a deployment availability check model and solution algorithm. The proposed framework is applied to an ES bidding problem in the DA and RT markets. The results indicate that deployment availability and operational performance of the ES are improved with the proposed data-driven AGC models compared to traditional benchmarks.

AGC signal model↗

RAYLEIGH–TAYLOR UNSTABLE FLAMES—FAST OR FASTER?

Rayleigh–Taylor (RT) unstable flames play a key role in the explosions of supernovae Ia. However, the dynamics of these flames are still not well understood. RT unstable flames are affected by both the RT instability of the flame front and by RT-generated turbulence. The coexistence of these factors complicates the choice of flame speed subgrid models for full-star Type Ia simulations. Both processes can stretch and wrinkle the flame surface, increasing its area and, therefore, the burning rate. In past research, subgrid models have been based on either the RT instability or turbulence setting the flame speed. We evaluate both models, checking their assumptions and their ability to correctly predict the turbulent flame speed. Specifically, we analyze a large parameter study of 3D direct numerical simulations of RT unstable model flames. This study varies both the simulation domain width and the gravity in order to probe a wide range of flame behaviors. We show that RT unstable flames are different from traditional turbulent flames: they are thinner rather than thicker when turbulence is stronger. We also show that none of the several different types of turbulent flame speed models accurately predicts measured flame speeds. In addition, we find that the RT flame speed model only correctly predicts the measured flame speed in a certain parameter regime. Finally, we propose that the formation of cusps may be the factor causing the flame to propagate more quickly than predicted by the RT model.

79 ASTRONOMY AND ASTROPHYSICS↗