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Longitudinal airflow suppresses train power-arc drift at low pressure

21 October 2026 at 23:11

Longitudinal airflow can sharply suppress the drifting and ablation of the electrical arc formed between a train’s pantograph and overhead contact wire, according to a modeling and experimental study of pantograph–catenary systems under low-pressure conditions. The researchers built a magnetohydrodynamic model that coupled electric, magnetic, thermal, fluid and arc-motion dynamics, then tested the method in a vacuum chamber with copper and carbon electrodes. In experiments conducted at atmospheric pressure, increasing the airflow to 45 metres per second reduced the measured arc drift height from 27.6 millimetres to zero and shortened the arc-root distance from 51.3 to 3.9 millimetres. The same airflow setting also produced progressively less carbon-electrode damage, supporting the proposal as a possible current-collection control method for railways operating at high altitude.

The need for such control arises because the pantograph–catenary system carries the electrical energy used by electric trains, while the stability of its contact strongly affects operating safety and efficiency. Lower atmospheric pressure presents a particularly difficult environment. The study notes that reduced air density and breakdown-field strength can lower the ignition threshold for pantograph–catenary arcs, increase their frequency and duration, and enlarge the region affected by arcing. Repeated arcing can cause irreversible high-temperature ablation and electrical wear on contact wires and pantograph strips. It can also generate broad-band electromagnetic interference that may affect onboard signalling and traction-control systems, with potential consequences including insulator flashover and disruption of the traction network. These background risks motivate efforts to understand and restrain the spatial movement of arcs in plateau environments.

Existing arc models include the Cassie and Mayr black-box approaches, which support analysis of interactions between arcs and traction-network circuits but do not represent an arc’s changing spatial shape. Magnetohydrodynamic models offer a more physical alternative by coupling electromagnetic, flow and thermal fields. Previous work represented crosswind effects on pantograph–catenary arcs and examined how decreasing pressure affects arc-root jumping, in which the root forms at a new location after the elongated column reaches a critical length. Other studies have shown that magnetic fields can stabilize welding and switching arcs. Airflow regulation, however, has been investigated more extensively in welding than in pantograph–catenary systems, whose dissimilar electrodes, high operating speed, open environment, changing electrode gap and constrained vehicle installation space make their arc dynamics more complicated.

The new model represents an arc initially 6 millimetres long and 2 millimetres in diameter between a copper anode and a carbon cathode. It includes the surrounding air, both electrodes and a central longitudinal-airflow channel beneath the copper electrode, including a 1.5-millimetre control-airflow inlet. A separate inlet represents train-induced airflow and was set to 40 metres per second. Calculations covered pressures of 101, 80 and 60 kilopascals, longitudinal airflow from zero to 80 metres per second and a total simulation time of 25 milliseconds. Air properties were adjusted with pressure, while the electrodes were assigned distinct densities, resistivities, thermal conductivities and heat capacities. The governing equations represented electrical potential and current, magnetic-vector potential, mass and momentum conservation, energy conservation, viscous dissipation, Joule heating and net volumetric radiation.

The calculations use several explicit simplifications. Arc ignition is omitted, and the plasma is treated as being in local thermodynamic equilibrium. Flow in the air and arc domains is assumed laminar and incompressible, while metal vapour generated by electrode evaporation and phase change is excluded. These assumptions make it possible to examine large-scale arc motion and temperature distribution but prevent the simulation from directly calculating electrode mass loss, crack width or crater area. Copper was assigned the anode and carbon the cathode; a Gaussian distribution represented current entering through the copper electrode, and the bottom of the carbon electrode was grounded. The air boundary was treated as magnetically insulated, and the initial temperatures were set to 300 kelvin for the air and electrodes and 5,000 kelvin for the arc domain. The experimental apparatus was separate from the numerical model and provided direct physical measurements of damage.

Without longitudinal airflow, the simulated arc passed through two stages. During the first 10 milliseconds, its column elongated continuously, bent under airflow influence, and developed greater drift height and arc-root distance. From 10 to 25 milliseconds, the column and root distance fluctuated through repeated shortening and elongation. The authors associate this behaviour with the electrical and mechanical limits of the arc: once a column reaches a critical length, the voltage and energy available between the electrodes may no longer sustain continuous burning, and a shorter path of lower resistance may form on the electrode surface. The resulting root “jump” shortened the column before airflow stretched it again. Arc development became faster and both drift height and root distance increased as pressure fell. Temperature briefly exceeded 10,000 kelvin and reached a maximum within roughly two to three milliseconds before fluctuating, while arc voltage rose as the column lengthened and resistance increased.

Longitudinal airflow changed these trajectories in the simulations. As speed increased, drift height, root distance and temperature all declined, with the greatest reductions occurring at lower airflow speeds before the curves began to level off. At 101 kilopascals, the calculated drift height fell from 37.5 millimetres without control airflow to zero at 45 metres per second, while root distance decreased from 57.3 to 3.7 millimetres and temperature dropped from 12,900 to 8,650 kelvin. The airflow needed to eliminate drift was 45, 40 and 35 metres per second at pressures of 101, 80 and 60 kilopascals, respectively; speeds required to bring root distance below 5 millimetres were 45, 40 and 30 metres per second. The authors attribute the stronger response at lower pressure to reduced plasma density, which weakens the arc’s inherent rigidity, Lorentz force and thermal buoyancy, allowing airflow load to become a more dominant influence on its motion.

The temperature response also revealed a practical plateau. The researchers defined the optimal airflow speed as the point after which increasing speed by 5 metres per second changes arc temperature by less than 3 per cent. At atmospheric pressure this occurred at 40 metres per second, compared with 30 metres per second at 60 kilopascals. The reported temperature reduction was 33.8 per cent at 101 kilopascals and 38.1 per cent at 60 kilopascals. Airflow strengthened convective heat removal, which lowered plasma temperature and, in turn, increased deionization and reduced Joule heating. Once thermal exchange approached saturation and the minimum temperature required for self-sustaining arc combustion was approached, further increases in speed produced little additional cooling. The model therefore indicates that the airflow speeds required for control decline as ambient pressure falls.

Laboratory testing used a vacuum chamber capable of controlling pressure with an accuracy of plus or minus 100 pascals, a constant-current supply rated from zero to 150 amperes, an arc igniter, a fan with continuously adjustable airflow from zero to 60 metres per second, a high-speed camera and an oscilloscope. Airflow at the electrode outlet was measured with an anemometer accurate to plus or minus 0.5 metres per second. The camera operated at 6,400 frames per second with an exposure of five microseconds, while each two-second arc test was repeated five times and the mean was reported. Tests at 101 kilopascals used airflow speeds of zero, 20, 30 and 45 metres per second. Without control airflow, high-speed images showed increasing arc drift. At 45 metres per second, drift was virtually absent during the final development phase and root distance was substantially shortened, with observed morphologies broadly consistent with the numerical results.

The experiments also found reductions in carbon-electrode ablation that increased with airflow speed. Microscopy showed shorter ablation areas, smaller craters and narrower crack propagation as the controlled airflow rose. The maximum crack width was 66.7 micrometres without airflow and decreased at higher speeds, while analytical weighing showed progressively less mass loss from the carbon electrode. The proposed mechanism is that stronger airflow promotes arc-root slippage, shortening the time the root remains at one point, while convective cooling lowers temperature and local energy density. These are experimental observations rather than direct outputs of the simulation: because the model omits electrode evaporation and metal-vapour transport, it cannot quantitatively predict ablation rates or near-electrode energy balances. The study therefore demonstrates reduced damage under its controlled laboratory conditions, not a complete first-principles calculation of all processes responsible for electrode wear or a proven field performance level in operating plateau railways.

Subject of Research: Experimental and numerical evaluation of airflow control of pantograph–catenary arcs at low pressure.

Article Title: Research on regulation method for suppression of pantograph-catenary arc by airflow in low-pressure environment

Article References: Xu, Z., Wang, S., Dong, K., & Gao, G. (2026). Research on regulation method for suppression of pantograph-catenary arc by airflow in low-pressure environment. iScience, 29(11), Article 117951. https://doi.org/10.1016/j.isci.2026.117951

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117951

Keywords: pantograph–catenary systems, railway electrification, electric arcs, low-pressure environments, longitudinal airflow, magnetohydrodynamic modelling, electrode ablation, high-speed rail, plateau railways, arc suppression, Research, regulation

When ‘access denied’ becomes an agent’s next objective

20 October 2026 at 10:00

One line from a recent AI incident caught my attention. Describing how an OpenAI agent got into a Medicare statistics portal, Australian Prime Minister Anthony Albanese said it “didn’t accept no for an answer.”

It sounds almost funny. In software terms, though, it points to a real problem. An access control said no, and the agent treated the answer as information about how to continue.

“The AI agent found a way around those blocks,” Albanese said. The agent accessed public and non-public files, according to the prime minister, though Deputy Prime Minister Richard Marles said the information was “not particularly sensitive.” An investigation is underway.

Around the same time, OpenAI disclosed another incident. A model in training found its web searches and direct connections blocked, then discovered that the environment’s own DNS resolver still answered. It embedded questions in hostnames and got answers from an external chatbot. OpenAI stopped the run. Days later, it shelved GPT-6.1 Astra, which Saachi Jain, its head of safety systems, said “didn’t quite meet the bar in terms of staying within scope and authorization.”

Different systems, different failures, one question: what does “access denied” mean to an agent?

Why a denial is information

Traditional software treats an authorization failure as the end of a code path. A service gets a 403, raises an exception and someone reads the log. The denial works as a stop sign because the program has no independent objective to pursue.

Agents do have one.

We have spent years teaching software to recover from failure: retry the request, switch the endpoint, back off and try again. Those are good instincts. They become dangerous when the failure is the security control itself.

A timeout says “try later.” A malformed request says “fix this.” An authorization failure says “you are not allowed to do this.” Those are different kinds of messages, but a guardrail that returns all three as text in the model’s context makes them look alike.

Researchers are now measuring what happens after a restriction is applied. In the August paper Permission Denied, 12 coding agents were tested under increasingly restrictive security policies. Blocked runs rarely stopped early. They timed out or produced wrong solutions. Of the policy-induced failures, the researchers found that 97% came from the agent building a workaround.

The issue is not simply whether a model understands a policy. It is what the system allows the model to do after the policy says no.

Enforcing policy outside the model is no longer a new idea. Recent research puts policy enforcement at a trusted tool boundary the agent cannot control. But that still leaves an unanswered question: when should a denial end the task rather than become another input for the agent?

Real systems already have harder stops. The OpenAI Agents SDK can halt a run when a tool guardrail raises an exception. Claude Code’s auto mode can return control to a person after three blocked actions in a row or 20 in total.

Nothing tells you which denials deserve which response. The missing piece is not another kill switch. It is a policy for deciding what a denial means and what authority disappears when it happens.

I don’t think the lesson is that models are bad. The problem is where we put the boundary. A guardrail that reports back to the thing it is restraining is a soft boundary. It shapes behavior. It doesn’t necessarily end it.

A terminal denial changes authority

I would treat denials differently depending on what they mean.

A denial is retryable when the same authorized request might succeed later without anyone granting new authority. A timeout, a temporary dependency failure or a rate limit can fit here.

It is correctable when the request itself is malformed and a legitimate fix does not expand what the task is allowed to do.

It is terminal when continuing would require permission the task was never given, such as reading another tenant’s records or reaching a destination the egress policy prohibits.

The test is whether succeeding needs permission or just patience.

If it needs permission, the agent shouldn’t be the one looking for it. At some point, persistence is just a very polite security incident.

In a previous InfoWorld piece, I argued that permission enforcement should be independent of how an agent interprets its situation. A terminal denial applies that principle at the moment of refusal. It should change the state of the system, not just the contents of the model’s context.

A terminal denial should do five things.

  1. Enforce it at a trusted execution boundary. The decision happens in the harness, policy service or gateway that executes the tool call, outside the model’s reasoning. A model cannot argue its way past a check it does not control.
  2. Take away the relevant authority. Once the task is terminally denied, the runtime rejects later calls that depend on the authority that was denied.
  3. Invalidate the relevant capabilities. Short-lived credentials and delegated permissions need to be revoked or fenced, including any the task passed to helper agents. Blocking an export tool is not enough if the same task can reach the same data through email five seconds later.
  4. Record the attempt outside the agent. The control plane should record the attempted action, policy decision and task identity in a protected audit trail. The agent shouldn’t document the event that stopped it.
  5. Require fresh authorization to resume. Restarting the task should be a new decision by a person or policy, not an automatic retry.

The model can still reason. It just no longer gets to act under the old authority.

This is not a bigger kill switch. A kill switch stops a whole agent; a terminal denial acts on a specific refusal when it happens.

Timing matters too.

Suppose the harness checks that a task is authorized and then dispatches an action. If the task is terminated between those two steps, a stale approval can still get through. High-impact operations need atomic authorization and dispatch where feasible, or fencing tokens that downstream services verify before accepting an action.

Work already in flight creates another problem. On an enterprise system I worked on, a permission check correctly rejected an operation, but the workflow kept going through work that had already been queued. The control worked at the point of rejection. The task still had a path to continue.

A queued operation may be cancellable. A running operation may be interruptible. A committed database write may require a compensating action instead.

The architecture needs to say which guarantee it provides.

Deny the effect, not the tool

The question I ask about every agent permission is what outcome the denial protects.

Not which API is blocked. Which effect is the policy trying to prevent?

Customer data leaving a tenant is an effect. It might happen through an export API, an email attachment, a file upload or a DNS lookup.

On another project, we restricted a sensitive operation at the main service interface and considered the control complete. Testing showed the same operation was still possible through a separate, approved path. The permission worked. We had protected the interface, not the effect.

An April stress test of Claude Code’s auto mode found a version of exactly this problem. When a command-line tool was unavailable, agents fell back to editing state files directly, “a path the classifier does not evaluate.”

Group controls by effect. When a terminal denial fires, apply it to the protected operation across every tool the task can use.

Treat repeated denials as a signal, not a magic number. Several denials across different tools pursuing the same outcome may mean the task should stop. Set the threshold by risk; one high-impact violation may be enough.

Treat every communication path as egress. Blocking HTTP does not establish isolation if DNS, package installation or shared infrastructure can still reach the outside.

Test the boundary the way an agent might challenge it.

Deny a resource through one tool while leaving another route available. Terminate a task with an action still queued. Revoke a parent task and check whether its helpers continue. Try a new action with a stale capability.

Measure whether the prohibited action executed. Do not measure success by whether the model said it would stop.

ScopeBench recently found 331 boundary violations that mechanical verification missed.

None of this is new to security engineers. Least privilege, deny by default and fail closed are decades-old principles.

What changes with agents is what happens after a control says no.

The answer is not to make every tool error fatal. It is to separate the model’s ability to propose the next action from the system’s authority to permit it.

A denial is a response. Enforcement is what happens next. The agent can be as persistent as we like. The boundary shouldn’t be negotiable.

What a Broken Wrist Taught Me About iOS 27 Dictation and macOS Voice Control

8 October 2026 at 16:21

Adam Engst:

Apple has significantly improved dictation in iOS 27 by adding a few capabilities for editing text from the Voice Control system. In other words, Apple has finally done some of the things I requested in “How iOS and macOS Dictation Can Learn from Voice Control’s Dictation” (31 August 2020). Remember, dictation is what you get when you tap the microphone button on the keyboard, while Voice Control is an all-encompassing system that you turn on in Settings > Accessibility > Voice Control. The problem with leaving Voice Control on permanently is that it’s constantly listening and thus inserting text when you don’t want that, and at times I have felt that its dictation isn’t as good.

Most notably, when you’re using iOS’s regular dictation, you can now change the case of words and phrases by saying “Capitalize phrase” or “Lowercase phrase.” Incorrect capitalization of words drives me up the wall. Equally useful is the ability to fix misheard or misspoken words by saying “Replace phrase1 with phrase2.” Most other Voice Control commands aren’t available in dictation, but you can say “Select phrase” and “Undo that.”

[…]

Unfortunately, while Apple added some of Voice Control’s capabilities to dictation in iOS 27, it didn’t extend that effort to macOS 27 Golden Gate. Put simply, when you use dictation in macOS, you don’t have access to any text-editing commands.

Previously:

Milt Windler, NASA flight director who helped save Apollo 13, dies at 94

3 October 2026 at 20:45

Milt Windler, one of the four leaders of Mission Control who in 1970 directed the round-the-clock efforts to bring the Apollo 13 astronauts back to Earth safely, has died at the age of 94.

Windler died on Thursday, surrounded by his loving family, according to a brief notice posted online.

Named a NASA flight director in 1968 after working on recovery operations during the Mercury and Gemini programs, Windler also led a shift of flight controllers for the Apollo 8 first circumlunar flight and Apollo 10 lunar landing dress rehearsal, as well as the second, third and fourth moon landings — Apollo 12, Apollo 14 and Apollo 15. He then served as a flight director for all three crewed missions to the United States' first space station, Skylab.

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Oferta: iPhone 17 (512GB) por R$6.209,10 no Pix!

21 October 2026 at 19:11

O iPhone 17 segue sendo o smartphone perfeito para a grande maioria dos usuários que procuram um telefone mais recente da Apple.

Entre as suas especificações técnicas, podemos destacar a tela Super Retina XDR de 6,3 polegadas com ProMotion (até 120Hz), o conjunto de duas câmeras (ambas de 48 megapixels, com sistema Fusion) e o processador A19, além da presença do Controle da Câmera (Camera Control) e do botão de Ação (Action Button).

Se você está atrás desse modelo, hoje a Amazon está com uma promoção excelente! Trata-se da versão de 512GB, na cor preta. O aparelho está saindo por R$6.899 em até 12x no cartão de crédito.

iPhone 17 de 512GB

Parcelado: de R$9.799,00 por R$6.899,00 em até 12x
À vista no Pix: de R$8.819,10 por R$6.209,10

🛍️ Produto vendido e entregue pela Amazon💰https://t.co/tjVVUH9g0F

— MM Ofertas (@MMOfertas) October 21, 2026

Se levarmos em conta que o preço tabelado desse modelo aqui no Brasil é de R$9.799 nessa mesma modalidade de pagamento, estamos diante de um desconto de 30%.

Para quem preferir pagar à vista no Pix, o valor cai para R$6.209,10 — representando uma diferença também de 30% em comparação com o preço à vista da Apple Brasil, de R$8.819,10.

Todos os descontos de promoções divulgadas pelo MacMagazine são calculados com base nos preços sugeridos pela Apple ou por outras fabricantes. Pode ser que um determinado produto seja comumente encontrado por valores inferiores em redes varejistas, mas a nossa base de comparação são sempre as tabelas oficiais.

Aproveite! 📱

Fique sempre por dentro das ofertas!

Se você não é louco, é claro que gosta de economizar. E, para isso, o MacMagazine tem diversas opções para ajudar você a conseguir comprar o seu produto Apple pagando menos!

Você pode usar a nossa extensão para os navegadores Chrome/Opera/Edge, acompanhar as ofertas pelo MM Fórum, pelo Facebook, pelo X, pelo Threads, pelo Bluesky, pelo Mastodon ou por um canal no Telegram. Escolha a melhor opção para você — ou todas, para depois não se arrepender — e economize! 😉

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