[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"insight-cdu-sizing-ai-data-halls":3},{"slug":4,"topic":5,"title":6,"excerpt":7,"author":8,"date":9,"featuredImageAlt":10,"primaryKeyword":11,"body":12,"seo":13,"faqs":16},"cdu-sizing-ai-data-halls","cooling","CDU Sizing for High-Density AI Data Halls","A practical guide to CDU sizing AI data hall, covering thermal design, CDUs, water, redundancy, testing and high-density GPU support.","W Land Editorial Team","2026-07-16","Technical diagram illustrating CDU sizing AI data hall for a private-power AI data center campus","CDU sizing AI data hall","\u003Cp>CDU sizing requires more than dividing hall MW by a catalogue capacity. The engineer must account for actual liquid heat load, diversity, temperatures, approach, pressure drop, pump duty, redundancy, controls, water quality and end-of-life expansion.\u003C\u002Fp>\n\u003Cp>The engineering basis begins with the actual GPU platform and thermal envelope. Rack density, liquid heat fraction and temperature limits should be confirmed before equipment is procured.\u003C\u002Fp>\n\u003Cp>For W Land’s planned West Texas AI energy campus, this topic should be resolved through a documented basis of design, a commercial responsibility matrix and an evidence-based diligence package. Any public capacity, schedule, cost or performance statement should remain qualified until the relevant site, equipment, permit and tenant decisions are complete.\u003C\u002Fp>\n\u003Ch2>Key takeaways\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>Choose rack-, row- or room-level CDU architecture.\u003C\u002Fli>\n\u003Cli>Define primary and secondary temperature envelopes.\u003C\u002Fli>\n\u003Cli>Set N+1 or distributed redundancy.\u003C\u002Fli>\n\u003Cli>Evaluate reliability, schedule, total installed cost and lifecycle operations—not a single headline metric.\u003C\u002Fli>\n\u003Cli>Keep the solution compatible with phased 25–50 MW deployment and a 100 MW Phase 1 campus.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>What the decision really involves\u003C\u002Fh2>\n\u003Cp>The first step is to define the operating outcome. For an AI data center, the requirement is not simply to install equipment with sufficient nameplate capacity. The complete system must maintain acceptable voltage, frequency, thermal conditions and maintainability through credible faults, maintenance events and expansion work.\u003C\u002Fp>\n\u003Cp>The project team should answer the following questions before design freeze:\u003C\u002Fp>\n\u003Col>\n\u003Cli>Choose rack-, row- or room-level CDU architecture.\u003C\u002Fli>\n\u003Cli>Define primary and secondary temperature envelopes.\u003C\u002Fli>\n\u003Cli>Set N+1 or distributed redundancy.\u003C\u002Fli>\n\u003Cli>Calculate hydraulic head and control range.\u003C\u002Fli>\n\u003Cli>Reserve bypass and maintenance isolation.\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Cp>The answers should be translated into single-line diagrams, thermal and hydraulic schematics, equipment data sheets, control narratives, operating modes and acceptance tests. That record is what allows a tenant, lender, insurer, owner’s engineer and permitting authority to evaluate the project consistently.\u003C\u002Fp>\n\u003Ch2>Decision matrix\u003C\u002Fh2>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Decision factor\u003C\u002Fth>\n\u003Cth>Configuration or reference\u003C\u002Fth>\n\u003Cth>Alternative or practical implication\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd>Thermal capacity\u003C\u002Ftd>\n\u003Ctd>kW\u002FMW\u003C\u002Ftd>\n\u003Ctd>Heat transfer rating\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Flow capacity\u003C\u002Ftd>\n\u003Ctd>Volume or mass flow\u003C\u002Ftd>\n\u003Ctd>Hydraulic delivery\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Approach temperature\u003C\u002Ftd>\n\u003Ctd>Primary-secondary difference\u003C\u002Ftd>\n\u003Ctd>Heat-exchanger performance\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Pump head\u003C\u002Ftd>\n\u003Ctd>Pressure budget\u003C\u002Ftd>\n\u003Ctd>Piping and cold plates\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Redundancy\u003C\u002Ftd>\n\u003Ctd>Spare unit\u002Fpump\u002Floop\u003C\u002Ftd>\n\u003Ctd>Fault-domain control\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\u003C\u002Ftable>\n\u003Cp>The matrix is a screening tool, not a substitute for engineering. Site conditions, tenant specifications, equipment availability and the adopted regulatory framework may change the result. The preferred solution should be supported by net site performance, lifecycle cost and failure-mode analysis.\u003C\u002Fp>\n\u003Ch2>Practical planning example\u003C\u002Fh2>\n\u003Cp>A 10 MW data hall with 90% liquid heat capture has roughly 9 MW of CDU duty before margin. Two 5 MW CDUs provide nameplate capacity but no redundancy; three 5 MW units may support N+1 depending on actual design conditions.\u003C\u002Fp>\n\u003Cp>A planning example should always state its assumptions. Electrical MW, thermal MW, MWh duration, gas heating-value basis, PUE, ambient condition, redundancy and end-of-life capacity are different metrics. Mixing them can make a concept appear more reliable or less expensive than it is.\u003C\u002Fp>\n\u003Cp>For a phased campus, the example should also be tested at the first block, full Phase 1 and ultimate master-plan conditions. A solution that works for one 25 MW block may produce excessive fault current, pipe length, cable count, control complexity or maintenance exposure at 500 MW.\u003C\u002Fp>\n\u003Ch2>Engineering, schedule and commercial implications\u003C\u002Fh2>\n\u003Ch3>Reliability and operations\u003C\u002Fh3>\n\u003Cp>The technology cooling system and facility cooling system must be separated by clear performance boundaries. Temperatures, flows, pressure, chemistry, heat-exchanger approach and allowable transients should be contractual.\u003C\u002Fp>\n\u003Cp>The operator should be involved before the design is issued for construction. Maintenance access, isolation boundaries, alarm priorities, spare parts, staffing and recovery procedures influence the architecture. A design that is efficient at full output but difficult to maintain can reduce actual availability.\u003C\u002Fp>\n\u003Ch3>Procurement and delivery\u003C\u002Fh3>\n\u003Cp>High-density halls still reject residual heat to air. The design should quantify the liquid heat fraction by platform and preserve room conditions for networking, power supplies, storage and service personnel.\u003C\u002Fp>\n\u003Cp>Long-lead procurement should use approved data sheets, witnessed factory tests, serial-number traceability and a controlled deviation process. The owner should receive editable drawings, calculations, configuration files, test data and operating manuals—not only scanned certificates.\u003C\u002Fp>\n\u003Ch3>Compliance and bankability\u003C\u002Fh3>\n\u003Cp>Cooling performance should be tested at the design envelope, including high ambient, degraded equipment and failure modes. Catalogue ratings at favorable temperatures are not sufficient.\u003C\u002Fp>\n\u003Cp>W Land and CITC can integrate the powered shell, facility water system, CDUs, distribution piping and heat rejection around the tenant’s actual GPU platform.\u003C\u002Fp>\n\u003Cp>The project should retain vendor neutrality unless a tenant or lender approves a proprietary standard. Equipment sourced through AiWB or CITC must satisfy the same U.S. technical, safety, cybersecurity, warranty and service requirements as domestic or European alternatives. The comparison should use landed, installed and risk-adjusted cost.\u003C\u002Fp>\n\u003Ch2>Common failure modes\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>Using nominal CDU rating at a different temperature approach.\u003C\u002Fli>\n\u003Cli>No pump-curve review.\u003C\u002Fli>\n\u003Cli>Ignoring fouling or filter pressure drop.\u003C\u002Fli>\n\u003Cli>CDUs cannot operate efficiently at partial load.\u003C\u002Fli>\n\u003Cli>Maintenance requires shutting an entire hall.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>These failures tend to appear at interfaces: vendor versus EPC, factory versus site, electrical versus mechanical, power plant versus data center, and commercial promise versus permit condition. W Land should maintain one interface register and one integrated schedule across all parties.\u003C\u002Fp>\n\u003Ch2>W Land implementation approach\u003C\u002Fh2>\n\u003Cp>W Land should address \u003Cstrong>CDU sizing AI data hall\u003C\u002Fstrong> through a gated process:\u003C\u002Fp>\n\u003Col>\n\u003Cli>\u003Cstrong>Requirement definition.\u003C\u002Fstrong> Confirm the tenant load, rack platform, reliability target, operating modes and expansion plan.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Concept screening.\u003C\u002Fstrong> Compare technically viable alternatives using the same site, ambient and commercial assumptions.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>U.S. engineering review.\u003C\u002Fstrong> Assign licensed engineers and specialist consultants to validate code, protection, permitting, fire and cybersecurity requirements.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Vendor qualification.\u003C\u002Fstrong> Require complete performance data, deviations, factory capability, service support and contractual guarantees.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Factory and site validation.\u003C\u002Fstrong> Use FAT, SAT and integrated systems testing tied to objective acceptance criteria.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Operational handover.\u003C\u002Fstrong> Deliver training, spares, controlled configurations, maintenance plans and tested emergency procedures.\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Cp>Final temperatures, flow, pressure, water chemistry, redundancy and controls must be approved by the GPU vendor, tenant, cooling OEM and licensed U.S. mechanical engineer.\u003C\u002Fp>\n\u003Ch2>Implementation checklist\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>Thermal load and heat fraction defined\u003C\u002Fli>\n\u003Cli>Temperature\u002Fapproach specified\u003C\u002Fli>\n\u003Cli>Hydraulic model completed\u003C\u002Fli>\n\u003Cli>Redundancy philosophy selected\u003C\u002Fli>\n\u003Cli>Water chemistry and filtration designed\u003C\u002Fli>\n\u003Cli>Controls and meter points defined\u003C\u002Fli>\n\u003Cli>Factory and site performance tests specified\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>Related W Land pages and articles\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Ca href=\"\u002Fdigital-infrastructure\u002Fequipment-supply-chain\u002Fcooling-equipment\" rel=\"noopener noreferrer\">Liquid Cooling & Thermal Management\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Fdigital-infrastructure\u002Fequipment-supply-chain\u002Fcooling-equipment\" rel=\"noopener noreferrer\">Cooling Equipment\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Fdigital-infrastructure\u002Fdata-center-site-development\" rel=\"noopener noreferrer\">AI-Ready Powered Shell\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Fcontact\" rel=\"noopener noreferrer\">Request an NDA Briefing\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Finsights\u002Fcooling\u002Fcool-100kw-150kw-gpu-racks\" rel=\"noopener noreferrer\">How to Cool 100 kW and 150 kW GPU Racks\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Finsights\u002Fcooling\u002Fdry-cooling-west-texas\" rel=\"noopener noreferrer\">Dry Cooling in the West Texas Climate\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"\u002Finsights\u002Fcooling\u002Fdirect-to-chip-vs-immersion\" rel=\"noopener noreferrer\">Direct-to-Chip vs. Immersion Cooling for AI Data Centers\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>Frequently asked questions\u003C\u002Fh2>\n\u003Ch3>What is a CDU?\u003C\u002Fh3>\n\u003Cp>A coolant distribution unit transfers heat between the technology cooling loop and facility cooling loop while controlling flow, pressure and temperature.\u003C\u002Fp>\n\u003Ch3>Where should CDUs be located?\u003C\u002Fh3>\n\u003Cp>At rack, row, hall or mechanical-room level depending on density, service and fault-domain strategy.\u003C\u002Fp>\n\u003Ch3>Why does temperature approach matter?\u003C\u002Fh3>\n\u003Cp>Heat-exchanger capacity depends on the difference between primary and secondary fluid temperatures.\u003C\u002Fp>\n\u003Ch3>Can a CDU be bypassed?\u003C\u002Fh3>\n\u003Cp>The design should provide isolation and maintenance arrangements consistent with the reliability target.\u003C\u002Fp>\n\u003Ch2>Next step\u003C\u002Fh2>\n\u003Cp>W Land is engaging with AI operators, hyperscale developers, energy partners, equipment suppliers and infrastructure investors regarding a planned West Texas private-power AI data center campus.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Request a 30-minute NDA briefing\u003C\u002Fstrong> to review the 100 MW Phase 1 development concept, 500 MW+ expansion strategy, equipment architecture and U.S. qualification process.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"\u002Fcontact\" rel=\"noopener noreferrer\">Request an NDA Briefing\u003C\u002Fa>\u003C\u002Fp>\n\u003Chr \u002F>\n\u003Ch2>Editorial qualification\u003C\u002Fh2>\n\u003Cp>This draft is educational and commercial content, not legal, engineering, permitting, fire-code or investment advice. Final public claims should be reviewed by W Land’s licensed U.S. engineers, permitting counsel, equipment vendors, tenant representatives and brand\u002Flegal teams. Standards, regulations, products and market conditions should be rechecked immediately before publication.\u003C\u002Fp>\n\u003Ch2>Editorial source notes\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.opencompute.org\u002Fdocuments\u002Focp-wp-l-lcdu-test-methodology-performance-rating-r1-pdf\" rel=\"noopener noreferrer\">Open Compute Project: Liquid-to-Liquid CDU Test Methodology\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.opencompute.org\u002Fdocuments\u002Focp-liquid-cooling-integration-and-logistics-white-paper-revision-1-0-1-pdf\" rel=\"noopener noreferrer\">Open Compute Project: Liquid Cooling Integration and Logistics\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fdocs.nvidia.com\u002Fdgx\u002Fdgxgb200-user-guide\u002Fhardware.html\" rel=\"noopener noreferrer\">NVIDIA DGX GB200 User Guide\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fdocs.nvidia.com\u002Fpdf\u002Fdgx-spod-gb300-ra.pdf\" rel=\"noopener noreferrer\">NVIDIA DGX SuperPOD GB300 Reference Architecture\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fblogs.nvidia.com\u002Fblog\u002Fblackwell-platform-water-efficiency-liquid-cooling-data-centers-ai-factories\u002F\" rel=\"noopener noreferrer\">NVIDIA: Blackwell, Liquid Cooling and Water Efficiency\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.opencompute.org\u002Fcommunity\u002Fcold-plate\" rel=\"noopener noreferrer\">Open Compute Project: Cold Plate Community\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n",{"metaTitle":14,"metaDescription":7,"canonicalURL":15},"CDU Sizing for High-Density AI Data Halls | W Land","\u002Finsights\u002Fcooling\u002Fcdu-sizing-ai-data-halls\u002F",[17,20,23,26],{"q":18,"a":19},"What is a CDU?","A coolant distribution unit transfers heat between the technology cooling loop and facility cooling loop while controlling flow, pressure and temperature.",{"q":21,"a":22},"Where should CDUs be located?","At rack, row, hall or mechanical-room level depending on density, service and fault-domain strategy.",{"q":24,"a":25},"Why does temperature approach matter?","Heat-exchanger capacity depends on the difference between primary and secondary fluid temperatures.",{"q":27,"a":28},"Can a CDU be bypassed?","The design should provide isolation and maintenance arrangements consistent with the reliability target."]