List of GoldSim Monte Carlo Customers
Seattle, 98104, WA,
United States
Since 2010, our global team of researchers has been studying GoldSim Monte Carlo customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased GoldSim Monte Carlo for Process Simulation from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using GoldSim Monte Carlo for Process Simulation include: BHP, a Australia based Oil, Gas and Chemicals organisation with 91304 employees and revenues of $51.26 billion, US Department of Energy, a United States based Government organisation with 15936 employees and revenues of $48.20 billion, Environment Agency, a United Kingdom based Government organisation with 10600 employees and revenues of $531.0 million and many others.
Contact us if you need a completed and verified list of companies using GoldSim Monte Carlo, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The GoldSim Monte Carlo customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
BHP | Oil, Gas and Chemicals | 91304 | $51.3B | Australia | GoldSim | GoldSim Monte Carlo | Process Simulation | 2013 | n/a |
In 2013, BHP, operating through its BMA coal operations, used GoldSim Monte Carlo to build water balance and mine water management models to support regulatory and planning requirements. The deployment used GoldSim Monte Carlo as a Process Simulation tool to underpin an Environmental Impact Statement for the Red Hill Mining Lease and to evaluate operational and closure water scenarios in Australia.
The implementation leveraged GoldSim mine water and water balance capabilities, configuring probabilistic Monte Carlo simulation runs and scenario libraries to capture variability in hydrology and operational inputs. Models were structured to produce time series and probabilistic discharge forecasts and to support sensitivity analysis across operational and closure case sets, reflecting standard Process Simulation workflows for water systems.
Model outputs were consumed by environmental planning and mine operations teams and provided inputs used in EIS design and discharge planning in 2013. Governance focused on scenario definition and results handoff to EIS authors and discharge planners, aligning modeling outputs with permitting and closure planning workflows rather than direct integrations with named enterprise systems.
|
 |
Environment Agency | Government | 10600 | $531M | United Kingdom | GoldSim | GoldSim Monte Carlo | Process Simulation | 2010 | n/a |
In 2010, the Environment Agency used GoldSim Monte Carlo models to explore engineered barrier system performance and support long-term safety and performance assessments for radioactive waste repositories in England and Wales. The deployment of GoldSim Monte Carlo falls within the Process Simulation category and was applied to technical safety assessment and regulatory evaluation functions within the agency.
Module usage including Radionuclide Transport and performance-assessment functionality is consistent with the Environment Agency report SC060055 and GoldSim documentation, and models used probabilistic Monte Carlo sampling to characterize uncertainty in feature, event and process interactions. Model configurations parameterized engineered barrier properties, radionuclide release pathways and scenario-based boundary conditions to enable sensitivity analyses and to identify the dominant FEPs influencing barrier performance.
The implementation supported regulatory safety cases and long-term performance assessments used by technical teams overseeing radioactive waste repositories in England and Wales. Governance integrated model outputs into assessment documentation and decision workflows, with iterative scenario testing to capture uncertainty and to prioritize features events and processes for monitoring and further study.
|
 |
US Department of Energy | Government | 15936 | $48.2B | United States | GoldSim | GoldSim Monte Carlo | Process Simulation | 2015 | n/a |
In 2015 the US Department of Energy Office of River Protection used GoldSim Monte Carlo for Process Simulation to develop an integrated system-level performance assessment for near-surface disposal. The GoldSim Monte Carlo implementation targeted the Hanford Integrated Disposal Facility and executed probabilistic runs to support uncertainty characterization and sensitivity analysis across disposal scenarios.
The implementation used system-level, probabilistic Process Simulation models, leveraging GoldSim Monte Carlo capabilities for Monte Carlo sampling, scenario ensembles, and time-dependent radionuclide transport modelling. Module usage is inferred to include Radionuclide Transport and probabilistic performance-assessment features drawn from WM2018 proceedings and GoldSim technical materials, and the modeling approach emphasized linked component models to represent engineered barriers and site processes.
Operational scope was centered on the Office of River Protection and the Hanford site, informing regulatory engagement, performance-assessment documentation, and decision-making workflows. The modelling effort informed regulatory compliance and decision-making between 2015–2018, embedding probabilistic Process Simulation into performance-assessment governance and review cycles.
|
Buyer Intent: Companies Evaluating GoldSim Monte Carlo
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||