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At least 1,459 records · Page 81

Security for Multimedia Space Data Distribution over the Internet

Distribution of interactive multimedia to remote investigators will be required for high quality science on the International Space Station (ISS). The Internet with the World Wide Web (WWW) and the JAVA environment are a good match for distribution of data, video and voice to remote science centers. Utilizing the "open" Internet in a secure manner is the major hurdle in making use of this cost effective, off-the-shelf, universal resource. This paper examines the major security threats to an Internet distribution system for payload data and the mitigation of these threats. A proposed security environment for the Space Station Biological Research Facility (SSBRP) is presented with a short description of the tools that have been implemented or planned. Formulating and implementing a security policy, firewalls, host hardware and software security are also discussed in this paper. Security is a vast topic and this paper can only give an overview of important issues. This paper postulates that a structured approach is required and stresses that security must be built into a network from the start. Ignoring security issues or putting them off until late in the development cycle can be disastrous.

Stone, Thom↗

Manual Asset Inventory: NASA Kennedy Space Center

The National Aeronautics and Aerospace Administration (NASA) relies in the security and protection of the information and information systems to know the devices that are connected to the Agency networks whether these are business, mission, research, or engineering devices. The Agency uses different Information Technology resources in order to do this process automatically, however, there are some devices that need to be reported manually. As a result of this, every month the Agency distributes among its Information System Owners (ISOs) the Manual Asset Inventory, a document that consists of a Microsoft Excel spreadsheet with twenty field descriptions cells that has to be filled out by the ISO of every Security Plan in the Center [fifty three in total] and uploaded into the IT Security Enterprise Data Warehouse (ITSEC-EDW).

Presentation↗

Transactive Energy Simulation Platform

TESP combines existing domain simulators in the electric power grid, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, and EnergyPlus for large buildings. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others; Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code; and Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP provides a method for other researchers and vendors to design transactive systems, and test them in a virtual environment. It allows customization of the key components by modifying Python code.

Source record↗

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

An ERCOT test system for market design studies

An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over highvoltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unrmed wind and solar power. Users can congure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modied or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Finally, detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SU-G-TeP1-12: Random Repainting as Mitigation for Scanned Ion Beam Interplay Effects

Purpose: Interference of dose application in scanned beam particle therapy and organ motion may lead to interplay effects with distorted dose to target volumes. Interplay effects depend on the speed and direction of the scanning beam, leading to fringed field edges (scanning parallel to organ motion direction) or over- and under-dosed regions (both directions are orthogonal). Current repainting methods can mitigate interplay effects, but are susceptible to artefacts when only a limited number of repaints are applied. In this study a random layered-repainting strategy was investigated. Methods: Mono-energetic proton beams were irradiated to a 10 ×10 cm{sup 2} scanned field at a Varian ProBeam facility. Applied dose was measured with a 2D amorphous silicon detector mounted on a motion platform (CIRS dynamic platform). Motion was considered with different cycles, directions and translations up to ±8 mm. Dose distributions were measured for a static case, regular repainting (repeated meander-like path) and random repainting. Latter was realized by randomly distributing single spot locations during irradiation for a given number of repaints. Efficiency of repainting was analyzed by comparison to the static case. A simulation tool based on treatment logs and motion information was developed to compare measurement results to expected dose distributions. Results: Regular repainting could reduce motion artefacts, but dose distortion was strongly dependent on motion direction. Random repainting with same number of repaints (N=4) showed superior results, independent of target movement direction, while introducing slight penalty on delivery times, caused by an increase of overall scanning travel distance. The simulation tool showed good agreement to measured results. Conclusion: The results demonstrate significant improvement in terms of dose conformity when layered repainting is applied in a randomized fashion. This allows for reduced target margins during treatment planning and limited number of repaints. A combination with e.g. respiratory gating is straight-forward. Authors are employees of Varian Medical Systems Particle Therapy GmbH.

43 PARTICLE ACCELERATORS↗

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet during atmospheric ascent is a major source of unsteady loading on launch vehicles that, in the past, has led to structural failures. Thus, determining accurate buffet forcing functions (BFFs) to properly predict the vehicle response to buffet is of vital importance in launch vehicle design. The state of the art for obtaining the BFFs relies on wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at sparse locations on a rigid, geometrically-scaled buffet model. To compute the BFFs, the outer mold line (OML) of the vehicle is mapped onto contiguous panels centered at the location of the PTs and the measured fluctuating pressures are integrated over the panels’ areas. To mitigate conservatism due to the assumption that the measured buffet pressures act in phase across each panel, coherence factors are applied, effectively reducing the integration areas and, therefore, the buffet forces. For coherence factors to provide the proper level of BFF attenuation, accurate knowledge of the spatial and temporal correlation of the buffet pressures is paramount. Unfortunately, even with hundreds of unsteady pressure transducers instrumenting the models, compromises must be made on the spatial resolution of the PTs. Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle, assuming that coherent structures propagate mostly in the longitudinal direction. As a result, the distribution of azimuthal/cross-stream correlation is not well known and its impact on the estimated BFFs is often neglected. To fill this and other knowledge gaps, extremely high spatial-resolution uPSP data were collected for three different production-design configurations of the Space Launch System in the NASA Ames Research Center Unitary Plan Wind Tunnel 11-Foot Transonic Wind Tunnel. Specifically, two cargo configurations, the Block 1 and Block 1B, and one crew configuration, the Block 1B crew, were surveyed at resolutions ranging from 600,000 to over 1 million uPSP measurement locations. To shed light on the temporal and spectral behavior of are presented. Several OML regions and flow features of interest are investigated, from theexpansion/shock on the Orion Multi-Purpose Crew Vehicle, to the terminal shock environment on the core stage, and the Strouhal shedding behind the boosters forward attach. The sensitivity of these environments to the vehicle attitude is examined. Furthermore, for selected panels,coherence factors that accurately capture the azimuthal coherence distribution of the buffetpressures are derived and their impact on the estimated BFFs is discussed. Finally, distributions of the local convection velocity and cross spectrum phase are presented.

buffet↗

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence

Increased coupling between critical infrastructure networks, such as power and communication systems, has important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several researchers have studied models of interdependent networks and reported that increased coupling can increase vulnerability. However, these conclusions come largely from models that have substantially different mechanisms of cascading failure, relative to those found in actual power and communication networks, and that do not capture the benefits of connecting systems with complementary capabilities. In order to understand the importance of these details, this paper compares network vulnerability in simple topological models and in models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid model shows a higher level of vulnerability, relative to the contagion model. Second, we compare a percolation model of topological cascading in coupled networks to three different models of power networks coupled to communication systems. Again, the more accurate models suggest very different conclusions than the percolation model. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the percolation model, in which zero coupling is optimal. Only in an extreme case, in which communication failures immediately cause grid failures, did we find that increased coupling can be harmful. Together, these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Moving from Information Assurance to Functional Assurance with Engineered Controls

Cyber threats to operational technology demand more than traditional IT defenses—they require full-spectrum mission assurance. Cyber-Informed Engineering (CIE) is an approach that embeds engineered controls into system design to ensure critical functions remain safe and reliable, even under attack. Unlike conventional cybersecurity tools, engineered controls act directly on physical processes to prevent unacceptable outcomes such as equipment damage or mission failure. This session will outline the CIE framework and share examples of consequence-based design that deliver true resilience, not just fail-safe behaviors. Attendees will learn how to integrate these principles into the engineering lifecycle to support resilient-by-design architectures and inform emerging standards. This talk sets the stage for the panel discussion on advancing CIE across sectors as digital and physical systems converge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. Here, the simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of a golden beam data set for the commissioning of a proton double-scattering system in a pencil-beam dose calculation algorithm

Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of RM-step thickness is required for accurate parameterization of the effective SAD. The GBD energy spread is given by a linear function of the exponential of the beam energy. Except for a few outliers, the measured parameters match the GBD within the specified tolerances in all of the four rooms investigated. For a SOBP field with a range of 15 g/cm{sup 2} and an air gap of 25 cm, the maximum difference in the 80%–20% lateral penumbra between the GBD-commissioned treatment-planning system and measurements in any of the four rooms is 0.5 mm. Conclusions: The beam model parameters of the double-scattering system can be parameterized with a limited set of equations and parameters. This GBD closely matches the measured dosimetric properties in four different rooms.

43 PARTICLE ACCELERATORS↗

Impact of Market Behavior, Fleet Composition, and Ancillary Services on Revenue Sufficiency

Revenue insufficiency, or the missing money problem, occurs when the revenues that generators earn from the market are not sufficient to cover both fixed and variable costs to remain in the market and/or justify investments in new capacity, which may be needed for reliability. The near-zero marginal cost of variable renewable generators further exacerbates these revenue challenges. Estimating the extent of the missing money problem in current electricity markets is an important, nontrivial task that requires representing both how the power system operates and how market participants behave. This paper explores the missing money problem using a production cost model that represented a simplified version of the Electric Reliability Council of Texas (ERCOT) energy-only market for the years 2012-2014. We evaluate how various market structures -- including market behavior, ancillary services, and changing fleet compositions -- affect net revenues in this ERCOT-like system. In most production cost modeling exercises, resources are assumed to offer their marginal capabilities at marginal costs. Although this assumption is reasonable for feasibility studies and long-term planning, it does not adequately consider the market behaviors that impact revenue sufficiency. In this work, we simulate a limited set of market participant strategic bidding behaviors by means of different sets of markups; these markups are applied to the true production costs of all gas generators, which are the most prominent generators in ERCOT. Results show that markups can help generators increase their net revenues overall, although net revenues may increase or decrease depending on the technology and the year under study. Results also confirm that conventional, variable-cost-based production cost simulations do not capture prices accurately, and this particular feature calls for proxies for strategic behaviors (e.g., markups) and more accurate representations of how electricity markets work. The analysis also shows that generators face revenue sufficiency challenges in this ERCOT-like energy-only market model; net revenues provided by the market in all base markup cases and sensitivity scenarios (except when a large fraction of the existing coal fleet is retired) are not sufficient to justify investments in new capacity for thermal and nuclear power units. Overall, the work described in this paper points to the need for improved behavioral models of electricity markets to more accurately study current and potential market design issues that could arise in systems with high penetrations of renewable generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-F-BRA-04: Prostate HDR Brachytherapy with Multichannel Robotic System

Purpose: High-dose-rate (HDR) brachytherapy is gradually becoming popular in treating patients with prostate cancers. However, placement of the HDR needles at desired locations into the patient is challenging. Application of robotic system may improve the accuracy of the clinical procedure. This experimental study is to evaluate the feasibility of using a multichannel robotic system for prostate HDR brachytherapy. Methods: In this experimental study, the robotic system employed was a 6-DOF Multichannel Image-guided Robotic Assistant for Brachytherapy (MIRAB), which was designed and fabricated for prostate seed implantation. The MIRAB has the provision of rotating 16 needles while inserting them. Ten prostate HDR brachytherapy needles were simultaneously inserted using MIRAB into a commercially available prostate phantom. After inserting the needles into the prostate phantom at desired locations, 2mm thick CT slices were obtained for dosimetric planning. HDR plan was generated using Oncetra planning system with a total prescription dose of 34Gy in 4 fractions. Plan quality was evaluated considering dose coverage to prostate and planning target volume (PTV), with 3mm margin around prostate, as well as the dose limit to the organs at risk (OARs) following the American Brachytherapy Society (ABS) guidelines. Results: From the CT scan, it is observed that the needles were inserted straight into the desired locations and they were adequately spaced and distributed for a clinically acceptable HDR plan. Coverage to PTV and prostate were about 91% (V100= 91%) and 96% (V100=96%), respectively. Dose to 1cc of urethra, rectum, and bladder were within the ABS specified limits. Conclusion: The MIRAB was able to insert multiple needles simultaneously into the prostate precisely. By controlling the MIRAB to insert all the ten utilized needles into the prostate phantom, we could achieve the robotic HDR brachytherapy successfully. Further study for assessing the system’s performance and reliability is in progress.

60 APPLIED LIFE SCIENCES↗

SU-E-J-164: An Investigation of a Low-Cost ‘dry’ Optical-CT Scanning System for 3D Dosimetry

Purpose: To characterize and explore the efficacy of a novel low-cost, lowfluid, broad-beam optical-CT system for 3D-dosimetry in radiochromic Presage dosimeters. Leading current optical-CT systems incorporate expensive glass-based telecentric lens technology, and a fluid bath with substantial amounts of fluid (which introduces an inconvenience factor) to minimize refraction artifacts. Here we introduce a novel system which addresses both these limitations by: (1) the use of Fresnel lenses in a telecentric arrangement, and (2) a ‘solid’ fluid bath which dramatically reduces the amount of fluid required for refractive-index (RI) matching. Materials Methods: A fresnel based telecentric optical-CT system was constructed which expands light from a single red LED source into a nominally parallel beam into which a cubic ‘dry-tank’ is placed. The drytank consists of a solid polyurethane cube (with the same RI as Presage) but containing a cylindrical cavity (11.5cm diameter × 11cm ) into which the dosimeter is placed for imaging. A narrow (1-3mm) gap between the walls of the dosimeter and dry-tank is filled with a fluid of similar RI. This arrangement reduces the amount of RI fluid from about 1000cc to 75cc, yielding substantial practical benefit in convenience and cost. The new system was evaluated in direct comparison against Eclipse planning system from a 4-field parallel-opposed treatmen Results: Gamma calculations of dose from DFOS-dry system versus Eclipse showed 92% and 97% agreement with 4mm/4% and 5mm/5% criteria, respectively, in the central 80% of dose distribution. Reconstructions showed some edge artifacts, as well as some dose underestimation towards the dosimeter edge. Conclusion: The implementation of Fresnel based ‘dry’ optical-CT for 3Ddosimetry would represent an important advance enhancing costeffectiveness and practical viability. The performance of the prototype presented here is not yet comparable to the state-of-the-art, but shows sufficient promise for further investigation to elevate image quality to match gold-standard optical-CT systems. This work was supported by NIH R01CA100835.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Power System Resilience Metrics Augmentation for Critical Load Prioritization

One of the major goals of new grid operation regimes, such as transactive energy systems (TESs), is to make the power grid more resilient to withstand natural or man-made disasters and potential reliability events, and to continue to serve the maximum number of its customers. But it is a well-known fact to system operators that not all customers are the same. This implies that any discussion of TESs’ impacts on the resilience of the power system should consider the needs of its critical customers (such as the power system operation centers, fire and police stations, and hospitals) over those of other customers. When evaluating the resilience of the system, bonus points must be awarded to any system that could maintain its power supply to critical customers during a disturbance that may cause an outage. This report discusses critical infrastructure (CI) as found in the literature and then categorizes it based on the field to which the operations belong (such as human life/safety-related, operations management, necessary city operation, industrial customers, etc.). Each of these CI categories is further divided into types of critical customers (e.g., the human life/safety-related category has different types of customers like hospitals, fire and police stations, etc.). The entire demand of each of the critical customer types is not categorized as critical load (CL); instead, only a portion of the total load of these critical customers is characterized as critical load. This is done based on the categories of equipment, the function of which is crucial in the operation of the overall facility. CL categorization is performed to provide the ratio of the critical load portion to the overall load , so that it can serve as a parameter in the resilience evaluation of the grid through a metrics-based approach. Such categorization is important as it helps to augment the existing quantifiable resilience metrics with CL categorization. The metrics for a power system need to not only consider how well a system performed during a disturbance event, but also how it reduced strain and supplied power to its CLs. The first step in this process is characterize CLs in the system. After CL characterization, the next step is the inclusion of these loads in the resilience metrics. To that end, in this report weight-based augmentation of resilience metrics is proposed, where certain customers (the ones that are categorized as critical) are assigned higher weights than others. Though an overview of assigning weights to customers is discussed, there is no one-size-fits-all approach for every power system. The decisions made about assigning such weights to customers vary greatly from one operator to another, based on their unique systems and the current and predicted states of critical customers. This decision-making can include the type of disturbance event, which might only affect certain parts of the system. In general, analyzing critical customers before an event helps understand system vulnerabilities. It also helps in planning and conducting operations during the event, evaluating system performance after the event, and supporting better planning for future events. An alternative to the current practices of managing the grid for outages is an innovative TES, which has the potential to provide a platform for including distributed energy resources for managing CLs. This report also describes how TES qualities can help (1) to maintain power supply to critical customers for uninterrupted operations and (2) to restore lost power supply to the critical customers rapidly.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗